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protein_in_food/Protein_folding.txt | Protein folding is the physical process by which a protein, after synthesis by a ribosome as a linear chain of amino acids, changes from an unstable random coil into a more ordered three-dimensional structure. This structure permits the protein to become biologically functional.
The folding of many proteins begins even during the translation of the polypeptide chain. The amino acids interact with each other to produce a well-defined three-dimensional structure, known as the protein's native state. This structure is determined by the amino-acid sequence or primary structure.
The correct three-dimensional structure is essential to function, although some parts of functional proteins may remain unfolded, indicating that protein dynamics are important. Failure to fold into a native structure generally produces inactive proteins, but in some instances, misfolded proteins have modified or toxic functionality. Several neurodegenerative and other diseases are believed to result from the accumulation of amyloid fibrils formed by misfolded proteins, the infectious varieties of which are known as prions. Many allergies are caused by the incorrect folding of some proteins because the immune system does not produce the antibodies for certain protein structures.
Denaturation of proteins is a process of transition from a folded to an unfolded state. It happens in cooking, burns, proteinopathies, and other contexts. Residual structure present, if any, in the supposedly unfolded state may form a folding initiation site and guide the subsequent folding reactions.
The duration of the folding process varies dramatically depending on the protein of interest. When studied outside the cell, the slowest folding proteins require many minutes or hours to fold, primarily due to proline isomerization, and must pass through a number of intermediate states, like checkpoints, before the process is complete. On the other hand, very small single-domain proteins with lengths of up to a hundred amino acids typically fold in a single step. Time scales of milliseconds are the norm, and the fastest known protein folding reactions are complete within a few microseconds. The folding time scale of a protein depends on its size, contact order, and circuit topology.
Understanding and simulating the protein folding process has been an important challenge for computational biology since the late 1960s.
Process of protein folding[edit]
Primary structure[edit]
The primary structure of a protein, its linear amino-acid sequence, determines its native conformation. The specific amino acid residues and their position in the polypeptide chain are the determining factors for which portions of the protein fold closely together and form its three-dimensional conformation. The amino acid composition is not as important as the sequence. The essential fact of folding, however, remains that the amino acid sequence of each protein contains the information that specifies both the native structure and the pathway to attain that state. This is not to say that nearly identical amino acid sequences always fold similarly. Conformations differ based on environmental factors as well; similar proteins fold differently based on where they are found.
Secondary structure[edit]
The alpha helix spiral formation
An anti-parallel beta pleated sheet displaying hydrogen bonding within the backbone
Formation of a secondary structure is the first step in the folding process that a protein takes to assume its native structure. Characteristic of secondary structure are the structures known as alpha helices and beta sheets that fold rapidly because they are stabilized by intramolecular hydrogen bonds, as was first characterized by Linus Pauling. Formation of intramolecular hydrogen bonds provides another important contribution to protein stability. α-helices are formed by hydrogen bonding of the backbone to form a spiral shape (refer to figure on the right). The β pleated sheet is a structure that forms with the backbone bending over itself to form the hydrogen bonds (as displayed in the figure to the left). The hydrogen bonds are between the amide hydrogen and carbonyl oxygen of the peptide bond. There exists anti-parallel β pleated sheets and parallel β pleated sheets where the stability of the hydrogen bonds is stronger in the anti-parallel β sheet as it hydrogen bonds with the ideal 180 degree angle compared to the slanted hydrogen bonds formed by parallel sheets.
Tertiary structure[edit]
The α-Helices and β-Sheets are commonly amphipathic, meaning they have a hydrophilic and a hydrophobic portion. This ability helps in forming tertiary structure of a protein in which folding occurs so that the hydrophilic sides are facing the aqueous environment surrounding the protein and the hydrophobic sides are facing the hydrophobic core of the protein. Secondary structure hierarchically gives way to tertiary structure formation. Once the protein's tertiary structure is formed and stabilized by the hydrophobic interactions, there may also be covalent bonding in the form of disulfide bridges formed between two cysteine residues. These non-covalent and covalent contacts take a specific topological arrangement in a native structure of a protein. Tertiary structure of a protein involves a single polypeptide chain; however, additional interactions of folded polypeptide chains give rise to quaternary structure formation.
Quaternary structure[edit]
Tertiary structure may give way to the formation of quaternary structure in some proteins, which usually involves the "assembly" or "coassembly" of subunits that have already folded; in other words, multiple polypeptide chains could interact to form a fully functional quaternary protein.
Driving forces of protein folding[edit]
All forms of protein structure summarized
Folding is a spontaneous process that is mainly guided by hydrophobic interactions, formation of intramolecular hydrogen bonds, van der Waals forces, and it is opposed by conformational entropy. The process of folding often begins co-translationally, so that the N-terminus of the protein begins to fold while the C-terminal portion of the protein is still being synthesized by the ribosome; however, a protein molecule may fold spontaneously during or after biosynthesis. While these macromolecules may be regarded as "folding themselves", the process also depends on the solvent (water or lipid bilayer), the concentration of salts, the pH, the temperature, the possible presence of cofactors and of molecular chaperones.
Proteins will have limitations on their folding abilities by the restricted bending angles or conformations that are possible. These allowable angles of protein folding are described with a two-dimensional plot known as the Ramachandran plot, depicted with psi and phi angles of allowable rotation.
Hydrophobic effect[edit]
Hydrophobic collapse. In the compact fold (to the right), the hydrophobic amino acids (shown as black spheres) collapse toward the center to become shielded from aqueous environment.
Protein folding must be thermodynamically favorable within a cell in order for it to be a spontaneous reaction. Since it is known that protein folding is a spontaneous reaction, then it must assume a negative Gibbs free energy value. Gibbs free energy in protein folding is directly related to enthalpy and entropy. For a negative delta G to arise and for protein folding to become thermodynamically favorable, then either enthalpy, entropy, or both terms must be favorable.
Entropy is decreased as the water molecules become more orderly near the hydrophobic solute.
Minimizing the number of hydrophobic side-chains exposed to water is an important driving force behind the folding process. The hydrophobic effect is the phenomenon in which the hydrophobic chains of a protein collapse into the core of the protein (away from the hydrophilic environment). In an aqueous environment, the water molecules tend to aggregate around the hydrophobic regions or side chains of the protein, creating water shells of ordered water molecules. An ordering of water molecules around a hydrophobic region increases order in a system and therefore contributes a negative change in entropy (less entropy in the system). The water molecules are fixed in these water cages which drives the hydrophobic collapse, or the inward folding of the hydrophobic groups. The hydrophobic collapse introduces entropy back to the system via the breaking of the water cages which frees the ordered water molecules. The multitude of hydrophobic groups interacting within the core of the globular folded protein contributes a significant amount to protein stability after folding, because of the vastly accumulated van der Waals forces (specifically London Dispersion forces). The hydrophobic effect exists as a driving force in thermodynamics only if there is the presence of an aqueous medium with an amphiphilic molecule containing a large hydrophobic region. The strength of hydrogen bonds depends on their environment; thus, H-bonds enveloped in a hydrophobic core contribute more than H-bonds exposed to the aqueous environment to the stability of the native state.
In proteins with globular folds, hydrophobic amino acids tend to be interspersed along the primary sequence, rather than randomly distributed or clustered together. However, proteins that have recently been born de novo, which tend to be intrinsically disordered, show the opposite pattern of hydrophobic amino acid clustering along the primary sequence.
Chaperones[edit]
Example of a small eukaryotic heat shock protein
Molecular chaperones are a class of proteins that aid in the correct folding of other proteins in vivo. Chaperones exist in all cellular compartments and interact with the polypeptide chain in order to allow the native three-dimensional conformation of the protein to form; however, chaperones themselves are not included in the final structure of the protein they are assisting in. Chaperones may assist in folding even when the nascent polypeptide is being synthesized by the ribosome. Molecular chaperones operate by binding to stabilize an otherwise unstable structure of a protein in its folding pathway, but chaperones do not contain the necessary information to know the correct native structure of the protein they are aiding; rather, chaperones work by preventing incorrect folding conformations. In this way, chaperones do not actually increase the rate of individual steps involved in the folding pathway toward the native structure; instead, they work by reducing possible unwanted aggregations of the polypeptide chain that might otherwise slow down the search for the proper intermediate and they provide a more efficient pathway for the polypeptide chain to assume the correct conformations. Chaperones are not to be confused with folding catalyst proteins, which catalyze chemical reactions responsible for slow steps in folding pathways. Examples of folding catalysts are protein disulfide isomerases and peptidyl-prolyl isomerases that may be involved in formation of disulfide bonds or interconversion between cis and trans stereoisomers of peptide group. Chaperones are shown to be critical in the process of protein folding in vivo because they provide the protein with the aid needed to assume its proper alignments and conformations efficiently enough to become "biologically relevant". This means that the polypeptide chain could theoretically fold into its native structure without the aid of chaperones, as demonstrated by protein folding experiments conducted in vitro; however, this process proves to be too inefficient or too slow to exist in biological systems; therefore, chaperones are necessary for protein folding in vivo. Along with its role in aiding native structure formation, chaperones are shown to be involved in various roles such as protein transport, degradation, and even allow denatured proteins exposed to certain external denaturant factors an opportunity to refold into their correct native structures.
A fully denatured protein lacks both tertiary and secondary structure, and exists as a so-called random coil. Under certain conditions some proteins can refold; however, in many cases, denaturation is irreversible. Cells sometimes protect their proteins against the denaturing influence of heat with enzymes known as heat shock proteins (a type of chaperone), which assist other proteins both in folding and in remaining folded. Heat shock proteins have been found in all species examined, from bacteria to humans, suggesting that they evolved very early and have an important function. Some proteins never fold in cells at all except with the assistance of chaperones which either isolate individual proteins so that their folding is not interrupted by interactions with other proteins or help to unfold misfolded proteins, allowing them to refold into the correct native structure. This function is crucial to prevent the risk of precipitation into insoluble amorphous aggregates. The external factors involved in protein denaturation or disruption of the native state include temperature, external fields (electric, magnetic), molecular crowding, and even the limitation of space (i.e. confinement), which can have a big influence on the folding of proteins. High concentrations of solutes, extremes of pH, mechanical forces, and the presence of chemical denaturants can contribute to protein denaturation, as well. These individual factors are categorized together as stresses. Chaperones are shown to exist in increasing concentrations during times of cellular stress and help the proper folding of emerging proteins as well as denatured or misfolded ones.
Under some conditions proteins will not fold into their biochemically functional forms. Temperatures above or below the range that cells tend to live in will cause thermally unstable proteins to unfold or denature (this is why boiling makes an egg white turn opaque). Protein thermal stability is far from constant, however; for example, hyperthermophilic bacteria have been found that grow at temperatures as high as 122 °C, which of course requires that their full complement of vital proteins and protein assemblies be stable at that temperature or above.
The bacterium E. coli is the host for bacteriophage T4, and the phage encoded gp31 protein (P17313) appears to be structurally and functionally homologous to E. coli chaperone protein GroES and able to substitute for it in the assembly of bacteriophage T4 virus particles during infection. Like GroES, gp31 forms a stable complex with GroEL chaperonin that is absolutely necessary for the folding and assembly in vivo of the bacteriophage T4 major capsid protein gp23.
Fold switching[edit]
Some proteins have multiple native structures, and change their fold based on some external factors. For example, the KaiB protein switches fold throughout the day, acting as a clock for cyanobacteria. It has been estimated that around 0.5–4% of PDB (Protein Data Bank) proteins switch folds.
Protein misfolding and neurodegenerative disease[edit]
Main article: Proteopathy
A protein is considered to be misfolded if it cannot achieve its normal native state. This can be due to mutations in the amino acid sequence or a disruption of the normal folding process by external factors. The misfolded protein typically contains β-sheets that are organized in a supramolecular arrangement known as a cross-β structure. These β-sheet-rich assemblies are very stable, very insoluble, and generally resistant to proteolysis. The structural stability of these fibrillar assemblies is caused by extensive interactions between the protein monomers, formed by backbone hydrogen bonds between their β-strands. The misfolding of proteins can trigger the further misfolding and accumulation of other proteins into aggregates or oligomers. The increased levels of aggregated proteins in the cell leads to formation of amyloid-like structures which can cause degenerative disorders and cell death. The amyloids are fibrillary structures that contain intermolecular hydrogen bonds which are highly insoluble and made from converted protein aggregates. Therefore, the proteasome pathway may not be efficient enough to degrade the misfolded proteins prior to aggregation. Misfolded proteins can interact with one another and form structured aggregates and gain toxicity through intermolecular interactions.
Aggregated proteins are associated with prion-related illnesses such as Creutzfeldt–Jakob disease, bovine spongiform encephalopathy (mad cow disease), amyloid-related illnesses such as Alzheimer's disease and familial amyloid cardiomyopathy or polyneuropathy, as well as intracellular aggregation diseases such as Huntington's and Parkinson's disease. These age onset degenerative diseases are associated with the aggregation of misfolded proteins into insoluble, extracellular aggregates and/or intracellular inclusions including cross-β amyloid fibrils. It is not completely clear whether the aggregates are the cause or merely a reflection of the loss of protein homeostasis, the balance between synthesis, folding, aggregation and protein turnover. Recently the European Medicines Agency approved the use of Tafamidis or Vyndaqel (a kinetic stabilizer of tetrameric transthyretin) for the treatment of transthyretin amyloid diseases. This suggests that the process of amyloid fibril formation (and not the fibrils themselves) causes the degeneration of post-mitotic tissue in human amyloid diseases. Misfolding and excessive degradation instead of folding and function leads to a number of proteopathy diseases such as antitrypsin-associated emphysema, cystic fibrosis and the lysosomal storage diseases, where loss of function is the origin of the disorder. While protein replacement therapy has historically been used to correct the latter disorders, an emerging approach is to use pharmaceutical chaperones to fold mutated proteins to render them functional.
Experimental techniques for studying protein folding[edit]
While inferences about protein folding can be made through mutation studies, typically, experimental techniques for studying protein folding rely on the gradual unfolding or folding of proteins and observing conformational changes using standard non-crystallographic techniques.
X-ray crystallography[edit]
Steps of X-ray crystallography
X-ray crystallography is one of the more efficient and important methods for attempting to decipher the three dimensional configuration of a folded protein. To be able to conduct X-ray crystallography, the protein under investigation must be located inside a crystal lattice. To place a protein inside a crystal lattice, one must have a suitable solvent for crystallization, obtain a pure protein at supersaturated levels in solution, and precipitate the crystals in solution. Once a protein is crystallized, X-ray beams can be concentrated through the crystal lattice which would diffract the beams or shoot them outwards in various directions. These exiting beams are correlated to the specific three-dimensional configuration of the protein enclosed within. The X-rays specifically interact with the electron clouds surrounding the individual atoms within the protein crystal lattice and produce a discernible diffraction pattern. Only by relating the electron density clouds with the amplitude of the X-rays can this pattern be read and lead to assumptions of the phases or phase angles involved that complicate this method. Without the relation established through a mathematical basis known as Fourier transform, the "phase problem" would render predicting the diffraction patterns very difficult. Emerging methods like multiple isomorphous replacement use the presence of a heavy metal ion to diffract the X-rays into a more predictable manner, reducing the number of variables involved and resolving the phase problem.
Fluorescence spectroscopy[edit]
Fluorescence spectroscopy is a highly sensitive method for studying the folding state of proteins. Three amino acids, phenylalanine (Phe), tyrosine (Tyr) and tryptophan (Trp), have intrinsic fluorescence properties, but only Tyr and Trp are used experimentally because their quantum yields are high enough to give good fluorescence signals. Both Trp and Tyr are excited by a wavelength of 280 nm, whereas only Trp is excited by a wavelength of 295 nm. Because of their aromatic character, Trp and Tyr residues are often found fully or partially buried in the hydrophobic core of proteins, at the interface between two protein domains, or at the interface between subunits of oligomeric proteins. In this apolar environment, they have high quantum yields and therefore high fluorescence intensities. Upon disruption of the protein's tertiary or quaternary structure, these side chains become more exposed to the hydrophilic environment of the solvent, and their quantum yields decrease, leading to low fluorescence intensities. For Trp residues, the wavelength of their maximal fluorescence emission also depend on their environment.
Fluorescence spectroscopy can be used to characterize the equilibrium unfolding of proteins by measuring the variation in the intensity of fluorescence emission or in the wavelength of maximal emission as functions of a denaturant value. The denaturant can be a chemical molecule (urea, guanidinium hydrochloride), temperature, pH, pressure, etc. The equilibrium between the different but discrete protein states, i.e. native state, intermediate states, unfolded state, depends on the denaturant value; therefore, the global fluorescence signal of their equilibrium mixture also depends on this value. One thus obtains a profile relating the global protein signal to the denaturant value. The profile of equilibrium unfolding may enable one to detect and identify intermediates of unfolding. General equations have been developed by Hugues Bedouelle to obtain the thermodynamic parameters that characterize the unfolding equilibria for homomeric or heteromeric proteins, up to trimers and potentially tetramers, from such profiles. Fluorescence spectroscopy can be combined with fast-mixing devices such as stopped flow, to measure protein folding kinetics, generate a chevron plot and derive a Phi value analysis.
Circular dichroism[edit]
Main article: Circular dichroism
Circular dichroism is one of the most general and basic tools to study protein folding. Circular dichroism spectroscopy measures the absorption of circularly polarized light. In proteins, structures such as alpha helices and beta sheets are chiral, and thus absorb such light. The absorption of this light acts as a marker of the degree of foldedness of the protein ensemble. This technique has been used to measure equilibrium unfolding of the protein by measuring the change in this absorption as a function of denaturant concentration or temperature. A denaturant melt measures the free energy of unfolding as well as the protein's m value, or denaturant dependence. A temperature melt measures the denaturation temperature (Tm) of the protein. As for fluorescence spectroscopy, circular-dichroism spectroscopy can be combined with fast-mixing devices such as stopped flow to measure protein folding kinetics and to generate chevron plots.
Vibrational circular dichroism of proteins[edit]
The more recent developments of vibrational circular dichroism (VCD) techniques for proteins, currently involving Fourier transform (FT) instruments, provide powerful means for determining protein conformations in solution even for very large protein molecules. Such VCD studies of proteins can be combined with X-ray diffraction data for protein crystals, FT-IR data for protein solutions in heavy water (D2O), or quantum computations.
Protein nuclear magnetic resonance spectroscopy[edit]
Main article: Protein NMR
Protein nuclear magnetic resonance (NMR) is able to collect protein structural data by inducing a magnet field through samples of concentrated protein. In NMR, depending on the chemical environment, certain nuclei will absorb specific radio-frequencies. Because protein structural changes operate on a time scale from ns to ms, NMR is especially equipped to study intermediate structures in timescales of ps to s. Some of the main techniques for studying proteins structure and non-folding protein structural changes include COSY, TOCSY, HSQC, time relaxation (T1 & T2), and NOE. NOE is especially useful because magnetization transfers can be observed between spatially proximal hydrogens are observed. Different NMR experiments have varying degrees of timescale sensitivity that are appropriate for different protein structural changes. NOE can pick up bond vibrations or side chain rotations, however, NOE is too sensitive to pick up protein folding because it occurs at larger timescale.
Timescale of protein structural changes matched with NMR experiments. For protein folding, CPMG Relaxation Dispersion (CPMG RD) and chemical exchange saturation transfer (CEST) collect data in the appropriate timescale.
Because protein folding takes place in about 50 to 3000 s CPMG Relaxation dispersion and chemical exchange saturation transfer have become some of the primary techniques for NMR analysis of folding. In addition, both techniques are used to uncover excited intermediate states in the protein folding landscape. To do this, CPMG Relaxation dispersion takes advantage of the spin echo phenomenon. This technique exposes the target nuclei to a 90 pulse followed by one or more 180 pulses. As the nuclei refocus, a broad distribution indicates the target nuclei is involved in an intermediate excited state. By looking at Relaxation dispersion plots the data collect information on the thermodynamics and kinetics between the excited and ground. Saturation Transfer measures changes in signal from the ground state as excited states become perturbed. It uses weak radio frequency irradiation to saturate the excited state of a particular nuclei which transfers its saturation to the ground state. This signal is amplified by decreasing the magnetization (and the signal) of the ground state.
The main limitations in NMR is that its resolution decreases with proteins that are larger than 25 kDa and is not as detailed as X-ray crystallography. Additionally, protein NMR analysis is quite difficult and can propose multiple solutions from the same NMR spectrum.
In a study focused on the folding of an amyotrophic lateral sclerosis involved protein SOD1, excited intermediates were studied with relaxation dispersion and Saturation transfer. SOD1 had been previously tied to many disease causing mutants which were assumed to be involved in protein aggregation, however the mechanism was still unknown. By using Relaxation Dispersion and Saturation Transfer experiments many excited intermediate states were uncovered misfolding in the SOD1 mutants.
Dual-polarization interferometry[edit]
Main article: Dual-polarization interferometry
Dual polarisation interferometry is a surface-based technique for measuring the optical properties of molecular layers. When used to characterize protein folding, it measures the conformation by determining the overall size of a monolayer of the protein and its density in real time at sub-Angstrom resolution, although real-time measurement of the kinetics of protein folding are limited to processes that occur slower than ~10 Hz. Similar to circular dichroism, the stimulus for folding can be a denaturant or temperature.
Studies of folding with high time resolution[edit]
The study of protein folding has been greatly advanced in recent years by the development of fast, time-resolved techniques. Experimenters rapidly trigger the folding of a sample of unfolded protein and observe the resulting dynamics. Fast techniques in use include neutron scattering, ultrafast mixing of solutions, photochemical methods, and laser temperature jump spectroscopy. Among the many scientists who have contributed to the development of these techniques are Jeremy Cook, Heinrich Roder, Harry Gray, Martin Gruebele, Brian Dyer, William Eaton, Sheena Radford, Chris Dobson, Alan Fersht, Bengt Nölting and Lars Konermann.
Proteolysis[edit]
Proteolysis is routinely used to probe the fraction unfolded under a wide range of solution conditions (e.g. fast parallel proteolysis (FASTpp).
Single-molecule force spectroscopy[edit]
Single molecule techniques such as optical tweezers and AFM have been used to understand protein folding mechanisms of isolated proteins as well as proteins with chaperones. Optical tweezers have been used to stretch single protein molecules from their C- and N-termini and unfold them to allow study of the subsequent refolding. The technique allows one to measure folding rates at single-molecule level; for example, optical tweezers have been recently applied to study folding and unfolding of proteins involved in blood coagulation. von Willebrand factor (vWF) is a protein with an essential role in blood clot formation process. It discovered – using single molecule optical tweezers measurement – that calcium-bound vWF acts as a shear force sensor in the blood. Shear force leads to unfolding of the A2 domain of vWF, whose refolding rate is dramatically enhanced in the presence of calcium. Recently, it was also shown that the simple src SH3 domain accesses multiple unfolding pathways under force.
Biotin painting[edit]
Biotin painting enables condition-specific cellular snapshots of (un)folded proteins. Biotin 'painting' shows a bias towards predicted Intrinsically disordered proteins.
Computational studies of protein folding[edit]
Computational studies of protein folding includes three main aspects related to the prediction of protein stability, kinetics, and structure. A 2013 review summarizes the available computational methods for protein folding.
Levinthal's paradox[edit]
In 1969, Cyrus Levinthal noted that, because of the very large number of degrees of freedom in an unfolded polypeptide chain, the molecule has an astronomical number of possible conformations. An estimate of 3 or 10 was made in one of his papers. Levinthal's paradox is a thought experiment based on the observation that if a protein were folded by sequential sampling of all possible conformations, it would take an astronomical amount of time to do so, even if the conformations were sampled at a rapid rate (on the nanosecond or picosecond scale). Based upon the observation that proteins fold much faster than this, Levinthal then proposed that a random conformational search does not occur, and the protein must, therefore, fold through a series of meta-stable intermediate states.
Energy landscape of protein folding[edit]
The energy funnel by which an unfolded polypeptide chain assumes its native structure
The configuration space of a protein during folding can be visualized as an energy landscape. According to Joseph Bryngelson and Peter Wolynes, proteins follow the principle of minimal frustration, meaning that naturally evolved proteins have optimized their folding energy landscapes, and that nature has chosen amino acid sequences so that the folded state of the protein is sufficiently stable. In addition, the acquisition of the folded state had to become a sufficiently fast process. Even though nature has reduced the level of frustration in proteins, some degree of it remains up to now as can be observed in the presence of local minima in the energy landscape of proteins.
A consequence of these evolutionarily selected sequences is that proteins are generally thought to have globally "funneled energy landscapes" (a term coined by José Onuchic) that are largely directed toward the native state. This "folding funnel" landscape allows the protein to fold to the native state through any of a large number of pathways and intermediates, rather than being restricted to a single mechanism. The theory is supported by both computational simulations of model proteins and experimental studies, and it has been used to improve methods for protein structure prediction and design. The description of protein folding by the leveling free-energy landscape is also consistent with the 2nd law of thermodynamics. Physically, thinking of landscapes in terms of visualizable potential or total energy surfaces simply with maxima, saddle points, minima, and funnels, rather like geographic landscapes, is perhaps a little misleading. The relevant description is really a high-dimensional phase space in which manifolds might take a variety of more complicated topological forms.
The unfolded polypeptide chain begins at the top of the funnel where it may assume the largest number of unfolded variations and is in its highest energy state. Energy landscapes such as these indicate that there are a large number of initial possibilities, but only a single native state is possible; however, it does not reveal the numerous folding pathways that are possible. A different molecule of the same exact protein may be able to follow marginally different folding pathways, seeking different lower energy intermediates, as long as the same native structure is reached. Different pathways may have different frequencies of utilization depending on the thermodynamic favorability of each pathway. This means that if one pathway is found to be more thermodynamically favorable than another, it is likely to be used more frequently in the pursuit of the native structure. As the protein begins to fold and assume its various conformations, it always seeks a more thermodynamically favorable structure than before and thus continues through the energy funnel. Formation of secondary structures is a strong indication of increased stability within the protein, and only one combination of secondary structures assumed by the polypeptide backbone will have the lowest energy and therefore be present in the native state of the protein. Among the first structures to form once the polypeptide begins to fold are alpha helices and beta turns, where alpha helices can form in as little as 100 nanoseconds and beta turns in 1 microsecond.
There exists a saddle point in the energy funnel landscape where the transition state for a particular protein is found. The transition state in the energy funnel diagram is the conformation that must be assumed by every molecule of that protein if the protein wishes to finally assume the native structure. No protein may assume the native structure without first passing through the transition state. The transition state can be referred to as a variant or premature form of the native state rather than just another intermediary step. The folding of the transition state is shown to be rate-determining, and even though it exists in a higher energy state than the native fold, it greatly resembles the native structure. Within the transition state, there exists a nucleus around which the protein is able to fold, formed by a process referred to as "nucleation condensation" where the structure begins to collapse onto the nucleus.
Modeling of protein folding[edit]
Folding@home uses Markov state models, like the one diagrammed here, to model the possible shapes and folding pathways a protein can take as it condenses from its initial randomly coiled state (left) into its native 3D structure (right).
De novo or ab initio techniques for computational protein structure prediction can be used for simulating various aspects of protein folding. Molecular dynamics (MD) was used in simulations of protein folding and dynamics in silico. First equilibrium folding simulations were done using implicit solvent model and umbrella sampling. Because of computational cost, ab initio MD folding simulations with explicit water are limited to peptides and very small proteins. MD simulations of larger proteins remain restricted to dynamics of the experimental structure or its high-temperature unfolding. Long-time folding processes (beyond about 1 millisecond), like folding of small-size proteins (about 50 residues) or larger, can be accessed using coarse-grained models.
Several large-scale computational projects, such as Rosetta@home, Folding@home and Foldit, target protein folding.
Long continuous-trajectory simulations have been performed on Anton, a massively parallel supercomputer designed and built around custom ASICs and interconnects by D. E. Shaw Research. The longest published result of a simulation performed using Anton is a 2.936 millisecond simulation of NTL9 at 355 K. The simulations are currently able to unfold and refold small (<150 amino acids residues) proteins and predict how mutations affect folding kinetics and stability.
In 2020 a team of researchers that used AlphaFold, an artificial intelligence (AI) program developed by DeepMind placed first in CASP. The team achieved a level of accuracy much higher than any other group. It scored above 90 for around two-thirds of the proteins in CASP's global distance test (GDT), a test that measures the degree to which a computational program predicted structure is similar to the lab experiment determined structure, with 100 being a complete match, within the distance cutoff used for calculating GDT.
AlphaFold's protein structure prediction results at CASP were described as "transformational" and "astounding". Some researchers noted that the accuracy is not high enough for a third of its predictions, and that it does not reveal the mechanism or rules of protein folding for the protein folding problem to be considered solved. Nevertheless, it is considered a significant achievement in computational biology and great progress towards a decades-old grand challenge of biology.
See also[edit]
Anfinsen's dogma
Chevron plot
Denaturation midpoint
Downhill folding
Folding (chemistry)
Phi value analysis
Potential energy of protein
Protein dynamics
Protein misfolding cyclic amplification
Protein structure prediction software
Proteopathy
Time-resolved mass spectrometry | biology | 147062 | https://sv.wikipedia.org/wiki/Proteinstruktur | Proteinstruktur | Strukturen för ett protein, kallat proteinstrukturen, är mycket viktig både för dess egenskaper och dess funktion. Proteinstrukturer är mycket komplicerade. Ribosomen tillverkar från början bara en lång kedja av aminosyror, som binds ihop en efter en av peptidbindningar. Processen som kedjan sedan genomgår för att finna den form i vilken proteinet kan fylla sin funktion är också mycket komplicerad och kallas proteinveckning.
Strukturnivåer
Aminosyrakedjan (även kallad polypeptidkedjan) som ett protein består av viks till en specifik tredimensionell form. Den slutliga formen bestäms av ordningen på aminosyrorna. Formen som ett protein naturligt viks till kallas för dess naturliga tillstånd. Formen har en avgörande betydelse för proteinets funktion.
Biokemister talar om fyra nivåer av struktur för ett protein:
Primärstruktur, ordningen på aminosyrorna
Sekundärstruktur, vikningar och spiraler som uppstår av vätebindningar mellan olika kedjedelar.
Tertiärstruktur, den övergripande formen hos en proteinmolekyl och förhållandet mellan de olika sekundärstrukturerna.
Kvartärstruktur, flera polypeptidkedjor.
Proteinets primära struktur
Den primära strukturen för proteiner är ordningen på aminosyrorna som finns med. Att bestämma ett proteins primära struktur är alltså att namnge varje aminosyra i ordning från början till slut. Denna struktur anger proteinets exakta kemiska uppbyggnad.
Konventionen för att bestämma ordningen på aminosyror är att N-terminalen (änden med en fri amingrupp) är till vänster och C-terminalen (änden med en fri karboxylgrupp) till höger. Den primära strukturen hålls ihop av kovalenta peptidbindningar som skapas under proteinsyntesen.
Medan primärstrukturen till stor del bestämmer proteinets tredimensionella form, är det mycket svårt att enbart med hjälp av primärstrukturen räkna ut sekundär- och tertiärstrukturen, eftersom det är så många processer som bidrar till att skapa dessa. Man kan dock gissa sig till strukturen för en del av kedjan om man vet strukturen för en liknande peptidkedja (homologistudier). Man kan också förutsäga sekundärstrukturen för vissa sekvenser med hjälp av simuleringar.
Proteinets sekundära struktur
Växelverkningar mellan olika delar av aminosyrakedjan ger upphov till större, väldefinierade strukturer. Dessa strukturer utgör proteinets sekundärstruktur. Sekundärstrukturen visar hur olika delar av kedjan, en bit ifrån varandra, sitter ihop. Dock beskriver den inte deras faktiska tredimensionella positioner; detta behöver man tertiärstrukturen för att veta.
Det finns två huvudsakliga sekundärstrukturer: alfa-helixar och beta-flak, som båda uppstår på grund av vätebindningar. Egenskaperna hos primärstrukturen är en av de bidragande faktorerna som avgör vilka sekundärstrukturer som uppstår. En viss sekundärstruktur kan förekomma på många olika ställen i ett protein, och aminosyraavsnitt med helt olika primärstruktur kan ge upphov till liknande sekundärstrukturer.
Alfa-helixar
Alfa-helixar är den vanligaste sekundärstrukturen. Aminosyrekedjan ”snurras” och skapar en spiral. Varje varv i denna spiral innehåller normalt 3,6 aminosyror. Skapandet av alfa-helixar är spontant och stabiliseras av vätebindningar. Olika aminosyror ingår i alfa-helixar med olika sannolikhet. I vissa fall är aminosyrornas sidokedjor (R-grupper) i vägen för varandra så att en alfa-helix inte kan bildas, så kallade steriska hinder. Aminosyran prolin ingår normalt inte i alfa-helixar på grund av dess begränsade rörlighet, medan aminosyran glycin å andra sidan är så extremt lättrörlig att den inte heller ofta deltar i alfa-helixar.
Beta-flak
Medan en alfa-helix består av en enskild linjär grupp av aminosyror så består betaflak av två eller fler olika delar av sträckor med åtminstone 5-10 aminosyror. Betaflak bildas av att olika delar av aminosyrekedjan binds till varandra. Vikningen och placeringen av sträckor av proteinets grundstomme (proteinet borträknat sidokedjorna) bredvid varandra för att forma beta-flaket skapas genom vätebindningar.
Sträckorna som beta-flaket består av kan antingen vara parallella eller anti-parallella. I parallella flak fortsätter närliggande peptidkedjor i samma riktning, medan i anti-parallella flak är närliggande kedjor arrangerade åt motsatt håll.
Loopar och random coils
Alfa-helixar och beta-flak binds ihop av korta avsnitt av väldefinierade loopar, där aminosyrakedjan svänger tvärt, eller random coils, som är mer ostrukturerade. Det finns många olika loopstrukturer, som även de stabiliseras av vätebindningar.
Proteinets tertiära struktur
Med ett proteins tertiära struktur menas den fullständiga tredimensionella strukturen av proteinet. Inkluderat i denna beskrivning är de rumsliga förhållandena olika sekundärstrukturer har till varandra inom en polypeptidkedja och hur dessa sekundärstrukturer själva hör ihop med den tredimensionella formen av proteinet.
Sekundärstrukturer av proteiner bildar ofta bestämda områden. Därför beskriver tertiärstrukturerna relationen av olika områden till varandra inom ett protein. Sådana sammansättningar av till exempel sekundärstruktur som är väldigt typiska och förekommer i många olika proteiner, kallas ibland för strukturmotiv (eng. Structural motif).
Denna struktur skapas av flera olika krafter. Den främsta kraften är hydrofoba interaktioner men vätebindningar, elektrostatiska interaktioner, van der Vaals-krafter och svavelbryggor spelar också en roll (se nedan).
Proteinets kvartära struktur
Många proteiner innehåller två eller flera proteinkedjor (polypeptidkedjor) som hålls ihop av samma icke-kovalenta krafter som stabiliserar tertiärstrukturerna i proteiner. De är alltså ihopsättningar av mer än en proteinmolekyl, eller monomer. Proteiner med flera proteinkedjor kallas för oligomeriska proteiner, eller multimerer.
Strukturen som formas av sammansättningen av de olika proteinkedjorna kallas för kvartärstrukturen. Oligomeriska proteiner kan bestå av flera identiska polypeptidkedjor eller flera olika sådana. Proteiner med identiska underenheter kallas homooligomerer, medan proteiner med flera olika polypeptidkedjor kallas för heterooligomerer.
Proteiner klassificeras vanligtvis i två större grupper:
Fiberproteiner (eller fibrösa proteiner)
Globulära proteiner
De fibrösa proteinerna kännetecknas av långa, raka kedjor. De är passiva strukturelement, i till exempel hår, naglar och bindevävnad). Fibrösa proteiner ger styrka och flexibilitet, är olösliga i vatten och har för det mesta bara en enda sekundärstruktur.
De globulära proteinerna bildar sfäriska molekyler och är "aktiva" proteiner (till exempel enzymer, transportproteiner). Globulära proteiner löser sig i vatten och har vanligtvis många olika sekundärstrukturer.
Krafter som kontrollerar proteinstrukturen
Vätebindningar
Polypeptider innehåller flera elektronegativa atomer både med och utan bundna väteatomer, både i grundstommarna och i R-grupperna (sidokedjorna). En elektronegativ atom som saknar ett väte kan bilda en vätebindning till en väteatom som är bunden till en annan elektronegativ atom, så att vätet i viss mån binds till båda de elektronegativa atomerna. En sådan elektronegativ atom är syre, som också finns tillsammans med väte i vattnet runt proteinet. Vätebindningar sker därför inte bara inom och mellan polypeptidkedjor utan också med det omgivande mediet. De andra två atomslagen som kan ge upphov till vätebindningar är fluor och kväve, varav den sistnämnda är ganska vanlig inom biokemin.
Hydrofoba krafter
Proteiner består av aminosyror som innehåller antingen hydrofila eller hydrofoba R-grupper. En hydrofil (vattenälskande) grupp är polär och interagerar med fördel med vattnet och andra polära grupper, medan en hydrofob, vattenavstötande, grupp är opolär och energimässigt gynnas av att interagera med andra opolära grupper. Dessa interaktioner spelar den största rollen i formandet av proteinstrukturen. Hydrofoba grupper återfinns oftast på proteinets insida, där de inte interagerar med vattnet. Dessa krafter begränsar vilka möjliga former ett protein kan vikas till.
Elektrostatiska krafter
Det finns även elektrostatiska krafter, det vill säga krafter mellan och inom laddningar och dipoler. Exempelvis understödjer reaktioner mellan olikt laddade R-grupper proteinveckning. Det sker även interaktioner mellan joniserade R-grupper och vattenmolekylen, som är en dipol, och även detta påverkar formen på proteinet.
van der Waals-krafter
Det finns både attraherande och repulsiva Londonkrafter som bestämmer proteinvikning. Londonkrafter är mycket svaga, men det enorma antalet sådana interaktioner som finns i stora proteinmolekyler gör att de påverkar proteinets utformning.
Vad har strukturen för betydelse?
Proteiner har olika funktioner att fylla, exempel på detta är att reagera med andra ämnen. Därför har formen stor betydelse för dess funktion. Om ett protein inte får den form som den skall ha för sin uppgift kommer proteinet inte att passa för det enzym den kodar för och därmed kommer reaktionen med andra ämnen antingen inte att ske överhuvudtaget eller inte på rätt sätt. Det är alltså formen på proteinet som ger den egenskaperna att kunna binda specifikt till vissa molekyler, exempelvis enzymer, och detta kan jämföras med en pusselbit där en korrekt formad protein kan passa in hos enzymet. De flesta enzymerna är dock flexibla och inte fasta vilket innebär att de kan anpassa sin form efter den reaktiva delen av proteinet som enzymet skall binda till. Beroende på hur aminosyrasekvensen ser ut får proteinet specifika funktioner den kan utföra. Aminosyrorna och miljön proteinet är syntetiserad i ger proteinet dess form.
Det finns många bioinformatiker och andra forskare som sysslar med att skapa proteiner på konstgjord väg. Dessa jobbar med att undersöka vilken form ett protein kommer att få eller vilket protein som behövs för att få en viss form.
Även om två proteiner har samma primärstruktur kan de få olika egenskaper om deras sekundär- och tertiärstrukturer är olika av någon anledning. Även om varje protein teoretiskt kan ha flera än en form, ses enbart en som dess ”riktiga” form, det vill säga den form som ger proteinets dess önskade egenskap.
Många problem kan uppstå av felaktiga proteinstrukturer. Utbytet av en hydrofobisk aminosyra (V) till en hydrofil aminosyra (E) i betakedjan av hemoglobin resulterar i sickle cell-anemi. Denna ändring av en enda aminosyra ändrar strukturen på enzymet så pass mycket att dess funktionalitet blir lidande, och personen som drabbas blir mycket sjuk. Ett annat exempel på felvikta proteiner är prioner som är skyldiga till bland annat galna ko-sjukan och Creutzfeldt–Jakobs sjukdom hos människor.
Med hjälp av kraftfulla datorer försöker man idag förutspå vilken form ett protein har i organismen utgående från dess primärstruktur. En forskare som vill skapa ett protein med vissa specifika egenskaper kan utgå från vilken form proteinet måste ha, och låta en dator räkna ut en primärstruktur som ger just den formen. För att öka beräkningshastigheten, och ge gemene man en möjlighet att hjälpa till vid forskningen har Stanford University startat projektet Folding@home, som bland annat forskar om Alzheimer, cancer och Parkinsons sjukdom
Se även
Biokemi
Bioteknik
Kemi
Biologi
Molekylärbiologi
Källor
King, Peptides and Proteins, Indiana State University School of Medicine
Horton et al., Principles of Biochemistry, Pearson Education, Upper Saddle River 2006.
Folding at homes hemsida
Referenser
Proteostas | swedish | 0.471093 |
protein_in_food/ProteinΓÇôprotein_interaction.txt |
Protein–protein interactions (PPIs) are physical contacts of high specificity established between two or more protein molecules as a result of biochemical events steered by interactions that include electrostatic forces, hydrogen bonding and the hydrophobic effect. Many are physical contacts with molecular associations between chains that occur in a cell or in a living organism in a specific biomolecular context.
Proteins rarely act alone as their functions tend to be regulated. Many molecular processes within a cell are carried out by molecular machines that are built from numerous protein components organized by their PPIs. These physiological interactions make up the so-called interactomics of the organism, while aberrant PPIs are the basis of multiple aggregation-related diseases, such as Creutzfeldt–Jakob and Alzheimer's diseases.
PPIs have been studied with many methods and from different perspectives: biochemistry, quantum chemistry, molecular dynamics, signal transduction, among others. All this information enables the creation of large protein interaction networks – similar to metabolic or genetic/epigenetic networks – that empower the current knowledge on biochemical cascades and molecular etiology of disease, as well as the discovery of putative protein targets of therapeutic interest.
Examples[edit]
Electron transfer proteins[edit]
Main article: Electron transfer protein
In many metabolic reactions, a protein that acts as an electron carrier binds to an enzyme that acts as its reductase. After it receives an electron, it dissociates and then binds to the next enzyme that acts as its oxidase (i.e. an acceptor of the electron). These interactions between proteins are dependent on highly specific binding between proteins to ensure efficient electron transfer. Examples: mitochondrial oxidative phosphorylation chain system components cytochrome c-reductase / cytochrome c / cytochrome c oxidase; microsomal and mitochondrial P450 systems.
In the case of the mitochondrial P450 systems, the specific residues involved in the binding of the electron transfer protein adrenodoxin to its reductase were identified as two basic Arg residues on the surface of the reductase and two acidic Asp residues on the adrenodoxin.
More recent work on the phylogeny of the reductase has shown that these residues involved in protein–protein interactions have been conserved throughout the evolution of this enzyme.
Signal transduction[edit]
Main article: Signal transduction
The activity of the cell is regulated by extracellular signals. Signal propagation inside and/or along the interior of cells depends on PPIs between the various signaling molecules. The recruitment of signaling pathways through PPIs is called signal transduction and plays a fundamental role in many biological processes and in many diseases including Parkinson's disease and cancer.
Membrane transport[edit]
Main article: Membrane transport
A protein may be carrying another protein (for example, from cytoplasm to nucleus or vice versa in the case of the nuclear pore importins).
Cell metabolism[edit]
Main article: Cell metabolism
In many biosynthetic processes enzymes interact with each other to produce small compounds or other macromolecules.
Muscle contraction[edit]
Main article: Muscle contraction
Physiology of muscle contraction involves several interactions. Myosin filaments act as molecular motors and by binding to actin enables filament sliding. Furthermore, members of the skeletal muscle lipid droplet-associated proteins family associate with other proteins, as activator of adipose triglyceride lipase and its coactivator comparative gene identification-58, to regulate lipolysis in skeletal muscle
Types[edit]
Main article: Multiprotein complex
To describe the types of protein–protein interactions (PPIs) it is important to consider that proteins can interact in a "transient" way (to produce some specific effect in a short time, like signal transduction) or to interact with other proteins in a "stable" way to form complexes that become molecular machines within the living systems. A protein complex assembly can result in the formation of homo-oligomeric or hetero-oligomeric complexes. In addition to the conventional complexes, as enzyme-inhibitor and antibody-antigen, interactions can also be established between domain-domain and domain-peptide. Another important distinction to identify protein–protein interactions is the way they have been determined, since there are techniques that measure direct physical interactions between protein pairs, named “binary” methods, while there are other techniques that measure physical interactions among groups of proteins, without pairwise determination of protein partners, named “co-complex” methods.
Homo-oligomers vs. hetero-oligomers[edit]
Homo-oligomers are macromolecular complexes constituted by only one type of protein subunit. Protein subunits assembly is guided by the establishment of non-covalent interactions in the quaternary structure of the protein. Disruption of homo-oligomers in order to return to the initial individual monomers often requires denaturation of the complex. Several enzymes, carrier proteins, scaffolding proteins, and transcriptional regulatory factors carry out their functions as homo-oligomers.
Distinct protein subunits interact in hetero-oligomers, which are essential to control several cellular functions. The importance of the communication between heterologous proteins is even more evident during cell signaling events and such interactions are only possible due to structural domains within the proteins (as described below).
Stable interactions vs. transient interactions[edit]
Stable interactions involve proteins that interact for a long time, taking part of permanent complexes as subunits, in order to carry out functional roles. These are usually the case of homo-oligomers (e.g. cytochrome c), and some hetero-oligomeric proteins, as the subunits of ATPase. On the other hand, a protein may interact briefly and in a reversible manner with other proteins in only certain cellular contexts – cell type, cell cycle stage, external factors, presence of other binding proteins, etc. – as it happens with most of the proteins involved in biochemical cascades. These are called transient interactions. For example, some G protein–coupled receptors only transiently bind to Gi/o proteins when they are activated by extracellular ligands, while some Gq-coupled receptors, such as muscarinic receptor M3, pre-couple with Gq proteins prior to the receptor-ligand binding. Interactions between intrinsically disordered protein regions to globular protein domains (i.e. MoRFs) are transient interactions.
Covalent vs. non-covalent[edit]
Main articles: Covalent bond and Non-covalent interactions
Covalent interactions are those with the strongest association and are formed by disulphide bonds or electron sharing. While rare, these interactions are determinant in some posttranslational modifications, as ubiquitination and SUMOylation. Non-covalent bonds are usually established during transient interactions by the combination of weaker bonds, such as hydrogen bonds, ionic interactions, Van der Waals forces, or hydrophobic bonds.
Role of water[edit]
Water molecules play a significant role in the interactions between proteins. The crystal structures of complexes, obtained at high resolution from different but homologous proteins, have shown that some interface water molecules are conserved between homologous complexes. The majority of the interface water molecules make hydrogen bonds with both partners of each complex. Some interface amino acid residues or atomic groups of one protein partner engage in both direct and water mediated interactions with the other protein partner. Doubly indirect interactions, mediated by two water molecules, are more numerous in the homologous complexes of low affinity. Carefully conducted mutagenesis experiments, e.g. changing a tyrosine residue into a phenylalanine, have shown that water mediated interactions can contribute to the energy of interaction. Thus, water molecules may facilitate the interactions and cross-recognitions between proteins.
Structure[edit]
Crystal structure of modified Gramicidin S determined by X-ray crystallography
NMR structure of cytochrome C illustrating its dynamics in solution
Main articles: X-ray crystallography and Nuclear magnetic resonance spectroscopy
The molecular structures of many protein complexes have been unlocked by the technique of X-ray crystallography. The first structure to be solved by this method was that of sperm whale myoglobin by Sir John Cowdery Kendrew. In this technique the angles and intensities of a beam of X-rays diffracted by crystalline atoms are detected in a film, thus producing a three-dimensional picture of the density of electrons within the crystal.
Later, nuclear magnetic resonance also started to be applied with the aim of unravelling the molecular structure of protein complexes. One of the first examples was the structure of calmodulin-binding domains bound to calmodulin. This technique is based on the study of magnetic properties of atomic nuclei, thus determining physical and chemical properties of the correspondent atoms or the molecules. Nuclear magnetic resonance is advantageous for characterizing weak PPIs.
Domains[edit]
Proteins hold structural domains that allow their interaction with and bind to specific sequences on other proteins:
Src homology 2 (SH2) domain Main article: SH2 domain
SH2 domains are structurally composed by three-stranded twisted beta sheet sandwiched flanked by two alpha-helices. The existence of a deep binding pocket with high affinity for phosphotyrosine, but not for phosphoserine or phosphothreonine, is essential for the recognition of tyrosine phosphorylated proteins, mainly autophosphorylated growth factor receptors. Growth factor receptor binding proteins and phospholipase Cγ are examples of proteins that have SH2 domains.
Src homology 3 (SH3) domain Main article: SH3 domain
Structurally, SH3 domains are constituted by a beta barrel formed by two orthogonal beta sheets and three anti-parallel beta strands. These domains recognize proline enriched sequences, as polyproline type II helical structure (PXXP motifs) in cell signaling proteins like protein tyrosine kinases and the growth factor receptor bound protein 2 (Grb2).
Phosphotyrosine-binding (PTB) domain Main article: PTB domain
PTB domains interact with sequences that contain a phosphotyrosine group. These domains can be found in the insulin receptor substrate.
LIM domain Main article: LIM domain
LIM domains were initially identified in three homeodomain transcription factors (lin11, is11, and mec3). In addition to this homeodomain proteins and other proteins involved in development, LIM domains have also been identified in non-homeodomain proteins with relevant roles in cellular differentiation, association with cytoskeleton and senescence. These domains contain a tandem cysteine-rich Zn-finger motif and embrace the consensus sequence CX2CX16-23HX2CX2CX2CX16-21CX2C/H/D. LIM domains bind to PDZ domains, bHLH transcription factors, and other LIM domains.
Sterile alpha motif (SAM) domain Main article: SAM domain
SAM domains are composed by five helices forming a compact package with a conserved hydrophobic core. These domains, which can be found in the Eph receptor and the stromal interaction molecule (STIM) for example, bind to non-SAM domain-containing proteins and they also appear to have the ability to bind RNA.
PDZ domain Main article: PDZ domain
PDZ domains were first identified in three guanylate kinases: PSD-95, DlgA and ZO-1. These domains recognize carboxy-terminal tri-peptide motifs (S/TXV), other PDZ domains or LIM domains and bind them through a short peptide sequence that has a C-terminal hydrophobic residue. Some of the proteins identified as having PDZ domains are scaffolding proteins or seem to be involved in ion receptor assembling and receptor-enzyme complexes formation.
FERM domain Main article: FERM domain
FERM domains contain basic residues capable of binding PtdIns(4,5)P2. Talin and focal adhesion kinase (FAK) are two of the proteins that present FERM domains.
Calponin homology (CH) domain Main article: Calponin homology domain
CH domains are mainly present in cytoskeletal proteins as parvin.
Pleckstrin homology domain Main article: Pleckstrin homology domain
Pleckstrin homology domains bind to phosphoinositides and acid domains in signaling proteins.
WW domain Main article: WW domain
WW domains bind to proline enriched sequences.
WSxWS motif
Found in cytokine receptors
Properties of the interface[edit]
The study of the molecular structure can give fine details about the interface that enables the interaction between proteins. When characterizing PPI interfaces it is important to take into account the type of complex.
Parameters evaluated include size (measured in absolute dimensions Å or in solvent-accessible surface area (SASA)), shape, complementarity between surfaces, residue interface propensities, hydrophobicity, segmentation and secondary structure, and conformational changes on complex formation.
The great majority of PPI interfaces reflects the composition of protein surfaces, rather than the protein cores, in spite of being frequently enriched in hydrophobic residues, particularly in aromatic residues. PPI interfaces are dynamic and frequently planar, although they can be globular and protruding as well. Based on three structures – insulin dimer, trypsin-pancreatic trypsin inhibitor complex, and oxyhaemoglobin – Cyrus Chothia and Joel Janin found that between 1,130 and 1,720 Å of surface area was removed from contact with water indicating that hydrophobicity is a major factor of stabilization of PPIs. Later studies refined the buried surface area of the majority of interactions to 1,600±350 Å. However, much larger interaction interfaces were also observed and were associated with significant changes in conformation of one of the interaction partners. PPIs interfaces exhibit both shape and electrostatic complementarity.
Regulation[edit]
Protein concentration, which in turn are affected by expression levels and degradation rates;
Protein affinity for proteins or other binding ligands;
Ligands concentrations (substrates, ions, etc.);
Presence of other proteins, nucleic acids, and ions;
Electric fields around proteins.
Occurrence of covalent modifications;
Experimental methods[edit]
Main article: Methods to investigate protein–protein interactions
There are a multitude of methods to detect them. Each of the approaches has its own strengths and weaknesses, especially with regard to the sensitivity and specificity of the method. The most conventional and widely used high-throughput methods are yeast two-hybrid screening and affinity purification coupled to mass spectrometry.
Principles of yeast and mammalian two-hybrid systems
Yeast two-hybrid screening[edit]
Main article: Two-hybrid screening
This system was firstly described in 1989 by Fields and Song using Saccharomyces cerevisiae as biological model. Yeast two hybrid allows the identification of pairwise PPIs (binary method) in vivo, in which the two proteins are tested for biophysically direct interaction. The Y2H is based on the functional reconstitution of the yeast transcription factor Gal4 and subsequent activation of a selective reporter such as His3. To test two proteins for interaction, two protein expression constructs are made: one protein (X) is fused to the Gal4 DNA-binding domain (DB) and a second protein (Y) is fused to the Gal4 activation domain (AD). In the assay, yeast cells are transformed with these constructs. Transcription of reporter genes does not occur unless bait (DB-X) and prey (AD-Y) interact with each other and form a functional Gal4 transcription factor. Thus, the interaction between proteins can be inferred by the presence of the products resultant of the reporter gene expression. In cases in which the reporter gene expresses enzymes that allow the yeast to synthesize essential amino acids or nucleotides, yeast growth under selective media conditions indicates that the two proteins tested are interacting. Recently, software to detect and prioritize protein interactions was published.
Despite its usefulness, the yeast two-hybrid system has limitations. It uses yeast as main host system, which can be a problem when studying proteins that contain mammalian-specific post-translational modifications. The number of PPIs identified is usually low because of a high false negative rate; and, understates membrane proteins, for example.
In initial studies that utilized Y2H, proper controls for false positives (e.g. when DB-X activates the reporter gene without the presence of AD-Y) were frequently not done, leading to a higher than normal false positive rate. An empirical framework must be implemented to control for these false positives. Limitations in lower coverage of membrane proteins have been overcoming by the emergence of yeast two-hybrid variants, such as the membrane yeast two-hybrid (MYTH) and the split-ubiquitin system, which are not limited to interactions that occur in the nucleus; and, the bacterial two-hybrid system, performed in bacteria;
Principle of tandem affinity purification
Affinity purification coupled to mass spectrometry[edit]
Main article: Mass spectrometry
Affinity purification coupled to mass spectrometry mostly detects stable interactions and thus better indicates functional in vivo PPIs. This method starts by purification of the tagged protein, which is expressed in the cell usually at in vivo concentrations, and its interacting proteins (affinity purification). One of the most advantageous and widely used methods to purify proteins with very low contaminating background is the tandem affinity purification, developed by Bertrand Seraphin and Matthias Mann and respective colleagues. PPIs can then be quantitatively and qualitatively analysed by mass spectrometry using different methods: chemical incorporation, biological or metabolic incorporation (SILAC), and label-free methods. Furthermore, network theory has been used to study the whole set of identified protein–protein interactions in cells.
Nucleic acid programmable protein array (NAPPA)[edit]
This system was first developed by LaBaer and colleagues in 2004 by using in vitro transcription and translation system. They use DNA template encoding the gene of interest fused with GST protein, and it was immobilized in the solid surface. Anti-GST antibody and biotinylated plasmid DNA were bounded in aminopropyltriethoxysilane (APTES)-coated slide. BSA can improve the binding efficiency of DNA. Biotinylated plasmid DNA was bound by avidin. New protein was synthesized by using cell-free expression system i.e. rabbit reticulocyte lysate (RRL), and then the new protein was captured through anti-GST antibody bounded on the slide. To test protein–protein interaction, the targeted protein cDNA and query protein cDNA were immobilized in a same coated slide. By using in vitro transcription and translation system, targeted and query protein was synthesized by the same extract. The targeted protein was bound to array by antibody coated in the slide and query protein was used to probe the array. The query protein was tagged with hemagglutinin (HA) epitope. Thus, the interaction between the two proteins was visualized with the antibody against HA.
Intragenic complementation[edit]
When multiple copies of a polypeptide encoded by a gene form a complex, this protein structure is referred to as a multimer. When a multimer is formed from polypeptides produced by two different mutant alleles of a particular gene, the mixed multimer may exhibit greater functional activity than the unmixed multimers formed by each of the mutants alone. In such a case, the phenomenon is referred to as intragenic complementation (also called inter-allelic complementation). Intragenic complementation has been demonstrated in many different genes in a variety of organisms including the fungi Neurospora crassa, Saccharomyces cerevisiae and Schizosaccharomyces pombe; the bacterium Salmonella typhimurium; the virus bacteriophage T4, an RNA virus and humans. In such studies, numerous mutations defective in the same gene were often isolated and mapped in a linear order on the basis of recombination frequencies to form a genetic map of the gene. Separately, the mutants were tested in pairwise combinations to measure complementation. An analysis of the results from such studies led to the conclusion that intragenic complementation, in general, arises from the interaction of differently defective polypeptide monomers to form a multimer. Genes that encode multimer-forming polypeptides appear to be common. One interpretation of the data is that polypeptide monomers are often aligned in the multimer in such a way that mutant polypeptides defective at nearby sites in the genetic map tend to form a mixed multimer that functions poorly, whereas mutant polypeptides defective at distant sites tend to form a mixed multimer that functions more effectively. Direct interaction of two nascent proteins emerging from nearby ribosomes appears to be a general mechanism for homo-oligomer (multimer) formation. Hundreds of protein oligomers were identified that assemble in human cells by such an interaction. The most prevalent form of interaction is between the N-terminal regions of the interacting proteins. Dimer formation appears to be able to occur independently of dedicated assembly machines. The intermolecular forces likely responsible for self-recognition and multimer formation were discussed by Jehle.
Other potential methods[edit]
Diverse techniques to identify PPIs have been emerging along with technology progression. These include co-immunoprecipitation, protein microarrays, analytical ultracentrifugation, light scattering, fluorescence spectroscopy, luminescence-based mammalian interactome mapping (LUMIER), resonance-energy transfer systems, mammalian protein–protein interaction trap, electro-switchable biosurfaces, protein–fragment complementation assay, as well as real-time label-free measurements by surface plasmon resonance, and calorimetry.
Computational methods[edit]
Text mining protocol.
Computational prediction of protein–protein interactions[edit]
The experimental detection and characterization of PPIs is labor-intensive and time-consuming. However, many PPIs can be also predicted computationally, usually using experimental data as a starting point. However, methods have also been developed that allow the prediction of PPI de novo, that is without prior evidence for these interactions.
Genomic context methods[edit]
The Rosetta Stone or Domain Fusion method is based on the hypothesis that interacting proteins are sometimes fused into a single protein in another genome. Therefore, we can predict if two proteins may be interacting by determining if they each have non-overlapping sequence similarity to a region of a single protein sequence in another genome.
The Conserved Neighborhood method is based on the hypothesis that if genes encoding two proteins are neighbors on a chromosome in many genomes, then they are likely functionally related (and possibly physically interacting).
The Phylogenetic Profile method is based on the hypothesis that if two or more proteins are concurrently present or absent across several genomes, then they are likely functionally related. Therefore, potentially interacting proteins can be identified by determining the presence or absence of genes across many genomes and selecting those genes which are always present or absent together.
Text mining methods[edit]
Further information: Text mining
Publicly available information from biomedical documents is readily accessible through the internet and is becoming a powerful resource for collecting known protein–protein interactions (PPIs), PPI prediction and protein docking. Text mining is much less costly and time-consuming compared to other high-throughput techniques. Currently, text mining methods generally detect binary relations between interacting proteins from individual sentences using rule/pattern-based information extraction and machine learning approaches. A wide variety of text mining applications for PPI extraction and/or prediction are available for public use, as well as repositories which often store manually validated and/or computationally predicted PPIs. Text mining can be implemented in two stages: information retrieval, where texts containing names of either or both interacting proteins are retrieved and information extraction, where targeted information (interacting proteins, implicated residues, interaction types, etc.) is extracted.
There are also studies using phylogenetic profiling, basing their functionalities on the theory that proteins involved in common pathways co-evolve in a correlated fashion across species. Some more complex text mining methodologies use advanced Natural Language Processing (NLP) techniques and build knowledge networks (for example, considering gene names as nodes and verbs as edges). Other developments involve kernel methods to predict protein interactions.
Machine learning methods[edit]
Machine-learning technique classification hierarchy.
Many computational methods have been suggested and reviewed for predicting protein–protein interactions. Prediction approaches can be grouped into categories based on predictive evidence: protein sequence, comparative genomics, protein domains, protein tertiary structure, and interaction network topology. The construction of a positive set (known interacting protein pairs) and a negative set (non-interacting protein pairs) is needed for the development of a computational prediction model. Prediction models using machine learning techniques can be broadly classified into two main groups: supervised and unsupervised, based on the labeling of input variables according to the expected outcome.
In 2005, integral membrane proteins of Saccharomyces cerevisiae were analyzed using the mating-based ubiquitin system (mbSUS). The system detects membrane proteins interactions with extracellular signaling proteins Of the 705 integral membrane proteins 1,985 different interactions were traced that involved 536 proteins. To sort and classify interactions a support vector machine was used to define high medium and low confidence interactions. The split-ubiquitin membrane yeast two-hybrid system uses transcriptional reporters to identify yeast transformants that encode pairs of interacting proteins.
In 2006, random forest, an example of a supervised technique, was found to be the most-effective machine learning method for protein interaction prediction. Such methods have been applied for discovering protein interactions on human interactome, specifically the interactome of Membrane proteins and the interactome of Schizophrenia-associated proteins.
As of 2020, a model using residue cluster classes (RCCs), constructed from the 3DID and Negatome databases, resulted in 96-99% correctly classified instances of protein–protein interactions. RCCs are a computational vector space that mimics protein fold space and includes all simultaneously contacted residue sets, which can be used to analyze protein structure-function relation and evolution.
Databases[edit]
Large scale identification of PPIs generated hundreds of thousands of interactions, which were collected together in specialized biological databases that are continuously updated in order to provide complete interactomes. The first of these databases was the Database of Interacting Proteins (DIP).
Primary databases collect information about published PPIs proven to exist via small-scale or large-scale experimental methods. Examples: DIP, Biomolecular Interaction Network Database (BIND), Biological General Repository for Interaction Datasets (BioGRID), Human Protein Reference Database (HPRD), IntAct Molecular Interaction Database, Molecular Interactions Database (MINT), MIPS Protein Interaction Resource on Yeast (MIPS-MPact), and MIPS Mammalian Protein–Protein Interaction Database (MIPS-MPPI).<
Meta-databases normally result from the integration of primary databases information, but can also collect some original data.
Prediction databases include many PPIs that are predicted using several techniques (main article). Examples: Human Protein–Protein Interaction Prediction Database (PIPs), Interlogous Interaction Database (I2D), Known and Predicted Protein–Protein Interactions (STRING-db), and Unified Human Interactive (UniHI).
The aforementioned computational methods all depend on source databases whose data can be extrapolated to predict novel protein–protein interactions. Coverage differs greatly between databases. In general, primary databases have the fewest total protein interactions recorded as they do not integrate data from multiple other databases, while prediction databases have the most because they include other forms of evidence in addition to experimental. For example, the primary database IntAct has 572,063 interactions, the meta-database APID has 678,000 interactions, and the predictive database STRING has 25,914,693 interactions. However, it is important to note that some of the interactions in the STRING database are only predicted by computational methods such as Genomic Context and not experimentally verified.
Interaction networks[edit]
Main article: Interactome
Schizophrenia PPI.
Information found in PPIs databases supports the construction of interaction networks. Although the PPI network of a given query protein can be represented in textbooks, diagrams of whole cell PPIs are frankly complex and difficult to generate.
One example of a manually produced molecular interaction map is the Kurt Kohn's 1999 map of cell cycle control. Drawing on Kohn's map, Schwikowski et al. in 2000 published a paper on PPIs in yeast, linking 1,548 interacting proteins determined by two-hybrid screening. They used a layered graph drawing method to find an initial placement of the nodes and then improved the layout using a force-based algorithm.
Bioinformatic tools have been developed to simplify the difficult task of visualizing molecular interaction networks and complement them with other types of data. For instance, Cytoscape is an open-source software widely used and many plugins are currently available. Pajek software is advantageous for the visualization and analysis of very large networks.
Identification of functional modules in PPI networks is an important challenge in bioinformatics. Functional modules means a set of proteins that are highly connected to each other in PPI network. It is almost similar problem as community detection in social networks. There are some methods such as Jactive modules and MoBaS. Jactive modules integrate PPI network and gene expression data where as MoBaS integrate PPI network and Genome Wide association Studies.
protein–protein relationships are often the result of multiple types of interactions or are deduced from different approaches, including co-localization, direct interaction, suppressive genetic interaction, additive genetic interaction, physical association, and other associations.
Signed interaction networks[edit]
The protein protein interactions are displayed in a signed network that describes what type of interactions that are taking place
Protein–protein interactions often result in one of the interacting proteins either being 'activated' or 'repressed'. Such effects can be indicated in a PPI network by "signs" (e.g. "activation" or "inhibition"). Although such attributes have been added to networks for a long time, Vinayagam et al. (2014) coined the term Signed network for them. Signed networks are often expressed by labeling the interaction as either positive or negative. A positive interaction is one where the interaction results in one of the proteins being activated. Conversely, a negative interaction indicates that one of the proteins being inactivated.
Protein–protein interaction networks are often constructed as a result of lab experiments such as yeast two-hybrid screens or 'affinity purification and subsequent mass spectrometry techniques. However these methods do not provide the layer of information needed in order to determine what type of interaction is present in order to be able to attribute signs to the network diagrams.
RNA interference screens[edit]
RNA interference (RNAi) screens (repression of individual proteins between transcription and translation) are one method that can be utilized in the process of providing signs to the protein–protein interactions. Individual proteins are repressed and the resulting phenotypes are analyzed. A correlating phenotypic relationship (i.e. where the inhibition of either of two proteins results in the same phenotype) indicates a positive, or activating relationship. Phenotypes that do not correlate (i.e. where the inhibition of either of two proteins results in two different phenotypes) indicate a negative or inactivating relationship. If protein A is dependent on protein B for activation then the inhibition of either protein A or B will result in a cell losing the service that is provided by protein A and the phenotypes will be the same for the inhibition of either A or B. If, however, protein A is inactivated by protein B then the phenotypes will differ depending on which protein is inhibited (inhibit protein B and it can no longer inactivate protein A leaving A active however inactivate A and there is nothing for B to activate since A is inactive and the phenotype changes). Multiple RNAi screens need to be performed in order to reliably appoint a sign to a given protein–protein interaction. Vinayagam et al. who devised this technique state that a minimum of nine RNAi screens are required with confidence increasing as one carries out more screens.
As therapeutic targets[edit]
Modulation of PPI is challenging and is receiving increasing attention by the scientific community. Several properties of PPI such as allosteric sites and hotspots, have been incorporated into drug-design strategies. Nevertheless, very few PPIs are directly targeted by FDA-approved small-molecule PPI inhibitors, emphasizing a huge untapped opportunity for drug discovery.
In 2014, Amit Jaiswal and others were able to develop 30 peptides to inhibit recruitment of telomerase towards telomeres by utilizing protein–protein interaction studies. Arkin and others were able to develop antibody fragment-based inhibitors to regulate specific protein-protein interactions.
As the "modulation" of PPIs not only includes the inhibition, but also the stabilization of quaternary protein complexes, molecules with this mechanism of action (so called molecular glues) are also intensively studied.
Examples[edit]
Tirobifan, inhibitor of the glycoprotein IIb/IIIa, used as a cardiovascular drug
Maraviroc, inhibitor of the CCR5-gp120 interaction, used as anti-HIV drug.
AMG-176, AZD5991, S64315, inhibitors of myeloid cell leukemia 1 (Mcl-1) protein and its interactions
See also[edit]
Glycan-protein interactions
3did
Allostery
Biological network
Biological machines
DIMA (database)
Enzyme catalysis
HitPredict
Human interactome
IsoBase
Multiprotein complex
Protein domain dynamics
Protein flexibility
Protein structure
Protein–protein interaction prediction
Protein–protein interaction screening
Systems biology | biology | 670452 | https://no.wikipedia.org/wiki/Proteinstrukturprediksjon | Proteinstrukturprediksjon | Proteinstrukturprediksjon er et aktivt forskningsfelt hvor målet er å forutsi den tredimensjonale strukturen til proteiner utfra sekvensen (primærstrukturen). Dette er en tverrfaglig disiplin i bioinformatikk som i tillegg til bioinformatiske metoder bruker kunnskap fra fysikk, matematikk, statistikk, visualisering, informatikk og kjemi.
I naturen finnes det utallige proteiner som deltar i alle prosesser som gjør at en organisme kan utvikle seg, vokse og vedlikeholde seg. Proteiner har dermed blitt studert nøye helt siden forskere oppdaget at det fantes proteiner. Den første strukturen ble bestemt i 1958, og siden den gang har mer enn 59 000 strukturer blitt eksperimentelt bestemt og publisert i den offentlige databasen Protein Data Bank.
Bare i menneskekroppen finnes det mellom 20 og 30 000 gener som koder for proteiner, og ett gen kan gi opphav til flere proteiner gjennom spleisingsprosessen som foregår i alle eukaryotiske organismer. Når det i tillegg finnes utallige andre arter og organismer, både planter og dyr, blir det klart at proteinene vi kjenner strukturen til bare utgjør en liten del av hva som faktisk finnes.
Strukturen til et protein henger nøye sammen med hvilken funksjon proteinet har, og det er dermed viktig å vite strukturen. I noen tilfeller er dette innen rekkevidde selv om bare sekvensen til proteinet er tilgjengelig, siden mange proteiner er beslektet og har samme funksjon i ulike organismer. Strukturen til et protein kan være nesten identisk mellom to beslektede arter, og hvis strukturen i ene arten er kjent kan denne brukes som et utgangspunkt for å gjette strukturen til det andre, tilsvarende proteinet. Dette kalles homologimodellering. Noen forskere mener at vi snart kan bruke bare homologimodellering for å finne strukturene til resten av proteinene vi ikke kjenner strukturen til. Nyere homologimodelleringsmetoder kan bruke flere proteiner som utgangspunkt dersom sekvensen indikerer at strukturen er en kombinasjon av ulike andre proteiner.
I noen tilfeller er det umulig å finne slektskap mellom en kjent struktur og proteinsekvensen som ikke har struktur. Da brukes ab initio-prediskjon. Ab initio er latin og brukes i betydningen fra begynnelsen. Metoder for å gjøre ab initio-prediksjon prøver å gjette strukturen kun utfra sekvensen. Noen aminosyrer har en tendens til å forme bestemte sekundærstrukturer, og denne informasjonen kan brukes til å danne et bilde av hvordan sekundærstrukturen i proteinet kan være. Eksisterende proteinstrukturer analyseres stadig for å prøve å finne generelle trekk som gjør dem stabile, og dette kan brukes i gjetningen av strukturer. Prediksjon av proteinstruktur når den eneste informasjonen tilgjengelig er sekvensen er et meget vanskelig problem å løse, og krever store ressurser.
Et beslektet problem er å prøve å finne den overordnede ordningen av proteinkjeden, kalt proteinets fold. Her er ikke målet å finne nøyaktige koordinater for alle aminosyrene, men å finne ut hvordan proteinkjeden krøller seg sammen. Denne informasjonen må være på plass før detaljer som nøyaktig hvor hver enkelt aminosyre befinner seg kan komme på plass. Dersom en kjent struktur er utgangspunkt kan denne jobben allerede være gjort.
Når plasseringen av selve ryggraden er utført, gjenstår fortsatt plasseringen av sidekjedene i aminosyrene. Funksjonen til et protein er nesten alltid avhengig av hvordan sidekjedene er plassert og jobber sammen. Det er ikke alltid nødvendig å finne en god plassering for alle sidekjedene, men de som er involvert i funksjonen til proteinet, som oftest i proteinets overflate, er viktige å få på plass. En kompliserende faktor her er at sidekjeder er fleksible og kan ha flere konformasjoner.
Referanser
Molekylærbiologi | norwegian_bokmål | 0.434102 |
protein_in_food/Protein_A.txt | Protein A is a 42 kDa surface protein originally found in the cell wall of the bacteria Staphylococcus aureus. It is encoded by the spa gene and its regulation is controlled by DNA topology, cellular osmolarity, and a two-component system called ArlS-ArlR. It has found use in biochemical research because of its ability to bind immunoglobulins. It is composed of five homologous Ig-binding domains that fold into a three-helix bundle. Each domain is able to bind proteins from many mammalian species, most notably IgGs. It binds the heavy chain within the Fc region of most immunoglobulins and also within the Fab region in the case of the human VH3 family. Through these interactions in serum, where IgG molecules are bound in the wrong orientation (in relation to normal antibody function), the bacteria disrupts opsonization and phagocytosis.
History[edit]
As a by-product of his work on type-specific staphylococcus antigens, Verwey reported in
1940 that a protein fraction prepared from extracts of these bacteria non-specifically precipitated rabbit antisera raised against different staphylococcus types. In 1958, Jensen confirmed Verwey's finding and showed that rabbit pre-immunization sera as well as normal human sera bound to the active component in the staphylococcus extract; he designated this component Antigen A (because it was found in fraction A of the extract) but thought it was a polysaccharide. The misclassification of the protein was the result of faulty tests, but it was not long thereafter (1962) that Löfkvist and Sjöquist corrected the error and confirmed that Antigen A was in fact a surface protein on the bacterial wall of certain strains of S. aureus. The Bergen group from Norway named the protein "Protein A" after the antigen fraction isolated by Jensen.
Protein A antibody binding[edit]
It has been shown via crystallographic refinement that the primary binding site for protein A is on the Fc region, between the CH2 and CH3 domains. In addition, protein A has been shown to bind human IgG molecules containing IgG F(ab')2 fragments from the human VH3 gene family.
Protein A can bind with strong affinity to the Fc portion of immunoglobulin of certain species as shown in the below table.
Species
Subclass
Binding
Human
IgA
variable
IgD
weak or none
IgE
weak or none
IgG1
strong
IgG2
strong
IgG3
weak or none
IgG4
strong
IgM
variable
Avian egg yolk
IgY
weak or none
Bovine
medium
Canine
medium
Goat
weak or none
Guinea pig
IgG1
strong
Hamster
weak
Horse
medium
Koala
weak or none
Llama
weak or none
Monkey (rhesus)
strong
Murine
IgG1
weak
IgG2a
strong
IgG2
medium to strong
IgG3
medium
IgM
variable
Pig
medium to strong
Rabbit
strong
Rat
IgG1
weak or none
IgG2a
weak or none
IgG2b
weak or none
IgG3
weak
Sheep
weak or none
Other antibody binding proteins[edit]
In addition to protein A, other immunoglobulin-binding bacterial proteins such as protein G, protein A/G and protein L are all commonly used to purify, immobilize or detect immunoglobulins.
Role in pathogenesis[edit]
As a pathogen, Staphylococcus aureus utilizes protein A, along with a host of other proteins and surface factors, to aid its survival and virulence. To this end, protein A plays a multifaceted role:
By binding the Fc portion of antibodies, protein A renders them inaccessible to the opsonins, thus impairing phagocytosis of the bacteria via immune cell attack.
Protein A facilitates the adherence of S. aureus to human von Willebrand factor (vWF)-coated surfaces, thus increasing the bacteria's infectiousness at the site of skin penetration.
Protein A can inflame lung tissue by binding to tumor necrosis factor 1 (TNFR-1) receptors. This interaction has been shown to play a key role in the pathogenesis of staphylococcal pneumonia.
Protein A has been shown to cripple humoral (antibody-mediated) immunity which in turn means that individuals can be repeatedly infected with S. aureus since they cannot mount a strong antibody response.
Protein A has been shown to promote the formation of biofilms both when the protein is covalently linked to the bacterial cell wall as well as in solution.
Protein A helps inhibit phagocytic engulfment and acts as an immunological disguise. Higher levels of protein A in different strains of S. aureus have been associated with nasal carriage of this bacteria.
Mutants of S. aureus lacking protein A are more efficiently phagocytosed in vitro, and mutants in infection models have diminished virulence.
Production[edit]
Protein A is produced and purified in industrial fermentation for use in immunology, biological research and industrial applications (see below). Natural (or native) protein A can be cultured in Staphylococcus aureus and contains the five homologous antibody binding regions described above and a C-terminal region for cell wall attachment. Today, protein A is more commonly produced recombinantly in Escherichia coli. (Brevibacillus has also been shown to be an effective host.) Recombinant versions of protein A also contain the five homologous antibody binding domains but may vary in other parts of the structure in order to facilitate coupling to porous substrates. Engineered versions of the protein are also available, the first of which was rProtein A, B4, C-CYS. Engineered versions are multimers (typically tetramers, pentamers or hexamers) of a single domain which has been modified to improve usability in industrial applications.
Research[edit]
Protein A is often coupled to other molecules such as a fluorescent dye, enzymes, biotin, colloidal gold or radioactive iodine without affecting the antibody binding site. Examples including protein A–gold (PAG) stain is used in immunogold labelling, fluorophore coupled protein A for immunofluorescence, and DNA docking strand coupled protein A for DNA-PAINT imaging. It is also widely utilized coupled to magnetic, latex and agarose beads.
Protein A is often immobilized onto a solid support and used as reliable method for purifying total IgG from crude protein mixtures such as serum or ascites fluid, or coupled with one of the above markers to detect the presence of antibodies. The first example of protein A being coupled to a porous bead for purification of IgG was published in 1972. Immunoprecipitation studies with protein A conjugated to beads are also commonly used to purify proteins or protein complexes indirectly through antibodies against the protein or protein complex of interest.
Role in industrial purification of antibodies[edit]
This process flow diagram shows how monoclonal antibodies are typically purified at industrial scale.
The first reference in the literature to a commercially available protein A chromatography resin appeared in 1976. Today, chromatographic separation using protein A immobilized on porous substrates is the most widely established method for purifying monoclonal antibodies (mAbs) from harvest cell culture supernatant. The choice of protein A as the preferred method is due to the high purity and yield which are easily and reliably achieved. This forms the basis for a general antibody purification "platform" which simplifies manufacturing operations and reduces the time and effort required to develop purification processes. A typical mAb purification process is shown at right. Albeit the long history of protein A chromatography for the production of antibodies, the process is still being improved today. Continuous chromatography, more precisely periodic counter-current chromatography, enormously increases the productivity of the purification step. | biology | 2469373 | https://sv.wikipedia.org/wiki/Aphos%20porosus | Aphos porosus | Aphos porosus är en fiskart som först beskrevs av Valenciennes, 1837. Aphos porosus ingår i släktet Aphos och familjen paddfiskar. IUCN kategoriserar arten globalt som livskraftig. Inga underarter finns listade i Catalogue of Life.
Källor
Externa länkar
Paddfiskar
porosus | swedish | 1.157103 |
protein_in_food/Protein_(nutrient).txt |
Proteins are essential nutrients for the human body. They are one of the building blocks of body tissue and can also serve as a fuel source. As a fuel, proteins provide as much energy density as carbohydrates: 4 kcal (17 kJ) per gram; in contrast, lipids provide 9 kcal (37 kJ) per gram. The most important aspect and defining characteristic of protein from a nutritional standpoint is its amino acid composition.
Proteins are polymer chains made of amino acids linked together by peptide bonds. During human digestion, proteins are broken down in the stomach to smaller polypeptide chains via hydrochloric acid and protease actions. This is crucial for the absorption of the essential amino acids that cannot be biosynthesized by the body.
There are nine essential amino acids which humans must obtain from their diet in order to prevent protein-energy malnutrition and resulting death. They are phenylalanine, valine, threonine, tryptophan, methionine, leucine, isoleucine, lysine, and histidine. There has been debate as to whether there are 8 or 9 essential amino acids. The consensus seems to lean towards 9 since histidine is not synthesized in adults. There are five amino acids which humans are able to synthesize in the body. These five are alanine, aspartic acid, asparagine, glutamic acid and serine. There are six conditionally essential amino acids whose synthesis can be limited under special pathophysiological conditions, such as prematurity in the infant or individuals in severe catabolic distress. These six are arginine, cysteine, glycine, glutamine, proline and tyrosine. Dietary sources of protein include grains, legumes, nuts, seeds, meats, dairy products, fish, eggs, edible insects, and seaweeds.
Protein functions in human body[edit]
Protein is a nutrient needed by the human body for growth and maintenance. Aside from water, proteins are the most abundant kind of molecules in the body. Protein can be found in all cells of the body and is the major structural component of all cells in the body, especially muscle. This also includes body organs, hair and skin. Proteins are also used in membranes, such as glycoproteins. When broken down into amino acids, they are used as precursors to nucleic acid, co-enzymes, hormones, immune response, cellular repair, and other molecules essential for life. Additionally, protein is needed to form blood cells.
Sources[edit]
Some sources of animal-based protein
Nutritional value and environmental impact of animal products, compared to agriculture overall
Categories
Contribution of farmed animal product [%]
Calories
18
Proteins
37
Land use
83
Greenhouse gases
58
Water pollution
57
Air pollution
56
Freshwater withdrawals
33
Protein occurs in a wide range of food. On a worldwide basis, plant protein foods contribute over 60% of the per capita supply of protein. In North America, animal-derived foods contribute about 70% of protein sources. Insects are a source of protein in many parts of the world. In parts of Africa, up to 50% of dietary protein derives from insects. It is estimated that more than 2 billion people eat insects daily.
Meat, dairy, eggs, soybeans, fish, whole grains, and cereals are sources of protein. Examples of food staples and cereal sources of protein, each with a concentration greater than 7%, are (in no particular order) buckwheat, oats, rye, millet, maize (corn), rice, wheat, sorghum, amaranth, and quinoa. Game meat is an affordable protein source in some countries.
Plant sources of proteins include legumes, nuts, seeds, grains, and some vegetables and fruits. Plant foods with protein concentrations greater than 7% include (but are not limited to) soybeans, lentils, kidney beans, white beans, mung beans, chickpeas, cowpeas, lima beans, pigeon peas, lupines, wing beans, almonds, Brazil nuts, cashews, pecans, walnuts, cotton seeds, pumpkin seeds, hemp seeds, sesame seeds, and sunflower seeds.
Photovoltaic-driven microbial protein production uses electricity from solar panels and carbon dioxide from the air to create fuel for microbes, which are grown in bioreactor vats and then processed into dry protein powders. The process makes highly efficient use of land, water and fertiliser.
Plant sources of protein.
People eating a balanced diet do not need protein supplements.
The table below presents food groups as protein sources.
Food source
Lysine
Threonine
Tryptophan
Sulfur-containingamino acids
Legumes
64
38
12
25
Cereals and whole grains
31
32
12
37
Nuts and seeds
45
36
17
46
Fruits
45
29
11
27
Animal
85
44
12
38
Colour key:
Protein source with highest density of respective amino acid.
Protein source with lowest density of respective amino acid.
Protein milkshakes, made from protein powder (center) and milk (left), are a common bodybuilding supplement
Protein powders – such as casein, whey, egg, rice, soy and cricket flour– are processed and manufactured sources of protein.
Testing in foods[edit]
The classic assays for protein concentration in food are the Kjeldahl method and the Dumas method. These tests determine the total nitrogen in a sample. The only major component of most food which contains nitrogen is protein (fat, carbohydrate and dietary fiber do not contain nitrogen). If the amount of nitrogen is multiplied by a factor depending on the kinds of protein expected in the food the total protein can be determined. This value is known as the "crude protein" content. The use of correct conversion factors is heavily debated, specifically with the introduction of more plant-derived protein products. However, on food labels the protein is calculated by the nitrogen multiplied by 6.25, because the average nitrogen content of proteins is about 16%. The Kjeldahl test is typically used because it is the method the AOAC International has adopted and is therefore used by many food standards agencies around the world, though the Dumas method is also approved by some standards organizations.
Accidental contamination and intentional adulteration of protein meals with non-protein nitrogen sources that inflate crude protein content measurements have been known to occur in the food industry for decades. To ensure food quality, purchasers of protein meals routinely conduct quality control tests designed to detect the most common non-protein nitrogen contaminants, such as urea and ammonium nitrate.
In at least one segment of the food industry, the dairy industry, some countries (at least the U.S., Australia, France and Hungary) have adopted "true protein" measurement, as opposed to crude protein measurement, as the standard for payment and testing: "True protein is a measure of only the proteins in milk, whereas crude protein is a measure of all sources of nitrogen and includes nonprotein nitrogen, such as urea, which has no food value to humans. ... Current milk-testing equipment measures peptide bonds, a direct measure of true protein." Measuring peptide bonds in grains has also been put into practice in several countries including Canada, the UK, Australia, Russia and Argentina where near-infrared reflectance (NIR) technology, a type of infrared spectroscopy is used. The Food and Agriculture Organization of the United Nations (FAO) recommends that only amino acid analysis be used to determine protein in, inter alia, foods used as the sole source of nourishment, such as infant formula, but also provides: "When data on amino acids analyses are not available, determination of protein based on total N content by Kjeldahl (AOAC, 2000) or similar method ... is considered acceptable."
The testing method for protein in beef cattle feed has grown into a science over the post-war years. The standard text in the United States, Nutrient Requirements of Beef Cattle, has been through eight editions over at least seventy years. The 1996 sixth edition substituted for the fifth edition's crude protein the concept of "metabolizeable protein", which was defined around the year 2000 as "the true protein absorbed by the intestine, supplied by microbial protein and undegraded intake protein".
The limitations of the Kjeldahl method were at the heart of the Chinese protein export contamination in 2007 and the 2008 China milk scandal in which the industrial chemical melamine was added to the milk or glutens to increase the measured "protein".
Protein quality[edit]
Further information: Protein quality and Amino acid score
The most important aspect and defining characteristic of protein from a nutritional standpoint is its amino acid composition. There are multiple systems which rate proteins by their usefulness to an organism based on their relative percentage of amino acids and, in some systems, the digestibility of the protein source. They include biological value, net protein utilization, and PDCAAS (Protein Digestibility Corrected Amino Acids Score) which was developed by the FDA as a modification of the Protein efficiency ratio (PER) method. The PDCAAS rating was adopted by the US Food and Drug Administration (FDA) and the Food and Agricultural Organization of the United Nations/World Health Organization (FAO/WHO) in 1993 as "the preferred 'best'" method to determine protein quality. These organizations have suggested that other methods for evaluating the quality of protein are inferior. In 2013 FAO proposed changing to Digestible Indispensable Amino Acid Score.
Digestion[edit]
Most proteins are decomposed to single amino acids by digestion in the gastro-intestinal tract.
Digestion typically begins in the stomach when pepsinogen is converted to pepsin by the action of hydrochloric acid, and continued by trypsin and chymotrypsin in the small intestine.
Before the absorption in the small intestine, most proteins are already reduced to single amino acid or peptides of several amino acids. Most peptides longer than four amino acids are not absorbed. Absorption into the intestinal absorptive cells is not the end. There, most of the peptides are broken into single amino acids.
Absorption of the amino acids and their derivatives into which dietary protein is degraded is done by the gastrointestinal tract. The absorption rates of individual amino acids are highly dependent on the protein source; for example, the digestibilities of many amino acids in humans, the difference between soy and milk proteins and between individual milk proteins, beta-lactoglobulin and casein. For milk proteins, about 50% of the ingested protein is absorbed between the stomach and the jejunum and 90% is absorbed by the time the digested food reaches the ileum. Biological value (BV) is a measure of the proportion of absorbed protein from a food which becomes incorporated into the proteins of the organism's body.
Newborn[edit]
Newborns of mammals are exceptional in protein digestion and assimilation in that they can absorb intact proteins at the small intestine. This enables passive immunity, i.e., transfer of immunoglobulins from the mother to the newborn, via milk.
Dietary requirements[edit]
An education campaign launched by the United States Department of Agriculture about 100 years ago, on cottage cheese as a lower-cost protein substitute for meat.
Average protein supply by region and origin
Considerable debate has taken place regarding issues surrounding protein intake requirements. The amount of protein required in a person's diet is determined in large part by overall energy intake, the body's need for nitrogen and essential amino acids, body weight and composition, rate of growth in the individual, physical activity level, the individual's energy and carbohydrate intake, and the presence of illness or injury. Physical activity and exertion as well as enhanced muscular mass increase the need for protein. Requirements are also greater during childhood for growth and development, during pregnancy, or when breastfeeding in order to nourish a baby or when the body needs to recover from malnutrition or trauma or after an operation.
Dietary recommendations[edit]
According to US & Canadian Dietary Reference Intake guidelines, women aged 19–70 need to consume 46 grams of protein per day while men aged 19–70 need to consume 56 grams of protein per day to minimize risk of deficiency. These Recommended Dietary Allowances (RDAs) were calculated based on 0.8 grams protein per kilogram body weight and average body weights of 57 kg (126 pounds) and 70 kg (154 pounds), respectively. However, this recommendation is based on structural requirements but disregards use of protein for energy metabolism. This requirement is for a normal sedentary person. In the United States, average protein consumption is higher than the RDA. According to results of the National Health and Nutrition Examination Survey (NHANES 2013–2014), average protein consumption for women ages 20 and older was 69.8 grams and for men 98.3 grams/day.
Active people[edit]
Several studies have concluded that active people and athletes may require elevated protein intake (compared to 0.8 g/kg) due to increase in muscle mass and sweat losses, as well as need for body repair and energy source. Suggested amounts vary from 1.2 to 1.4 g/kg for those doing endurance exercise to as much as 1.6-1.8 g/kg for strength exercise and up to 2.0 g/kg/day for older people, while a proposed maximum daily protein intake would be approximately 25% of energy requirements i.e. approximately 2 to 2.5 g/kg. However, many questions still remain to be resolved.
In addition, some have suggested that athletes using restricted-calorie diets for weight loss should further increase their protein consumption, possibly to 1.8–2.0 g/kg, in order to avoid loss of lean muscle mass.
Aerobic exercise protein needs[edit]
Endurance athletes differ from strength-building athletes in that endurance athletes do not build as much muscle mass from training as strength-building athletes do. Research suggests that individuals performing endurance activity require more protein intake than sedentary individuals so that muscles broken down during endurance workouts can be repaired. Although the protein requirement for athletes still remains controversial (for instance see Lamont, Nutrition Research Reviews, pages 142 - 149, 2012), research does show that endurance athletes can benefit from increasing protein intake because the type of exercise endurance athletes participate in still alters the protein metabolism pathway. The overall protein requirement increases because of amino acid oxidation in endurance-trained athletes. Endurance athletes who exercise over a long period (2–5 hours per training session) use protein as a source of 5–10% of their total energy expended. Therefore, a slight increase in protein intake may be beneficial to endurance athletes by replacing the protein lost in energy expenditure and protein lost in repairing muscles. One review concluded that endurance athletes may increase daily protein intake to a maximum of 1.2–1.4 g per kg body weight.
Anaerobic exercise protein needs[edit]
Research also indicates that individuals performing strength training activity require more protein than sedentary individuals. Strength-training athletes may increase their daily protein intake to a maximum of 1.4–1.8 g per kg body weight to enhance muscle protein synthesis, or to make up for the loss of amino acid oxidation during exercise. Many athletes maintain a high-protein diet as part of their training. In fact, some athletes who specialize in anaerobic sports (e.g., weightlifting) believe a very high level of protein intake is necessary, and so consume high protein meals and also protein supplements.
Special populations[edit]
Protein allergies[edit]
Main article: Food allergy
A food allergy is an abnormal immune response to proteins in food. The signs and symptoms may range from mild to severe. They may include itchiness, swelling of the tongue, vomiting, diarrhea, hives, trouble breathing, or low blood pressure. These symptoms typically occurs within minutes to one hour after exposure. When the symptoms are severe, it is known as anaphylaxis. The following eight foods are responsible for about 90% of allergic reactions: cow's milk, eggs, wheat, shellfish, fish, peanuts, tree nuts and soy.
Chronic kidney disease[edit]
While there is no conclusive evidence that a high protein diet can cause chronic kidney disease, there is a consensus that people with this disease should decrease consumption of protein. According to one 2009 review updated in 2018, people with chronic kidney disease who reduce protein consumption have less likelihood of progressing to end stage kidney disease. Moreover, people with this disease while using a low protein diet (0.6 g/kg/d - 0.8 g/kg/d) may develop metabolic compensations that preserve kidney function, although in some people, malnutrition may occur.
Phenylketonuria[edit]
Individuals with phenylketonuria (PKU) must keep their intake of phenylalanine – an essential amino acid – extremely low to prevent a mental disability and other metabolic complications. Phenylalanine is a component of the artificial sweetener aspartame, so people with PKU need to avoid low calorie beverages and foods with this ingredient.
Excess consumption[edit]
See also: Protein poisoning
The U.S. and Canadian Dietary Reference Intake review for protein concluded that there was not sufficient evidence to establish a Tolerable upper intake level, i.e., an upper limit for how much protein can be safely consumed.
When amino acids are in excess of needs, the liver takes up the amino acids and deaminates them, a process converting the nitrogen from the amino acids into ammonia, further processed in the liver into urea via the urea cycle. Excretion of urea occurs via the kidneys. Other parts of the amino acid molecules can be converted into glucose and used for fuel. When food protein intake is periodically high or low, the body tries to keep protein levels at an equilibrium by using the "labile protein reserve" to compensate for daily variations in protein intake. However, unlike body fat as a reserve for future caloric needs, there is no protein storage for future needs.
Excessive protein intake may increase calcium excretion in urine, occurring to compensate for the pH imbalance from oxidation of sulfur amino acids. This may lead to a higher risk of kidney stone formation from calcium in the renal circulatory system. One meta-analysis reported no adverse effects of higher protein intakes on bone density. Another meta-analysis reported a small decrease in systolic and diastolic blood pressure with diets higher in protein, with no differences between animal and plant protein.
High protein diets have been shown to lead to an additional 1.21 kg of weight loss over a period of 3 months versus a baseline protein diet in a meta-analysis. Benefits of decreased body mass index as well as HDL cholesterol were more strongly observed in studies with only a slight increase in protein intake rather where high protein intake was classified as 45% of total energy intake. Detrimental effects to cardiovascular activity were not observed in short-term diets of 6 months or less. There is little consensus on the potentially detrimental effects to healthy individuals of a long-term high protein diet, leading to caution advisories about using high protein intake as a form of weight loss.
The 2015–2020 Dietary Guidelines for Americans (DGA) recommends that men and teenage boys increase their consumption of fruits, vegetables and other under-consumed foods, and that a means of accomplishing this would be to reduce overall intake of protein foods. The 2015 - 2020 DGA report does not set a recommended limit for the intake of red and processed meat. While the report acknowledges research showing that lower intake of red and processed meat is correlated with reduced risk of cardiovascular diseases in adults, it also notes the value of nutrients provided from these meats. The recommendation is not to limit intake of meats or protein, but rather to monitor and keep within daily limits the sodium (< 2300 mg), saturated fats (less than 10% of total calories per day), and added sugars (less than 10% of total calories per day) that may be increased as a result of consumption of certain meats and proteins. While the 2015 DGA report does advise for a reduced level of consumption of red and processed meats, the 2015-2020 DGA key recommendations recommend that a variety of protein foods be consumed, including both vegetarian and non-vegetarian sources of protein.
Protein deficiency[edit]
A child in Nigeria during the Biafra War with kwashiorkor – one of the three protein energy malnutrition ailments affecting over 10 million children in developing countries.
Main article: Protein-energy malnutrition
Protein deficiency and malnutrition (PEM) can lead to variety of ailments including Intellectual disability and kwashiorkor. Symptoms of kwashiorkor include apathy, diarrhea, inactivity, failure to grow, flaky skin, fatty liver, and edema of the belly and legs. This edema is explained by the action of lipoxygenase on arachidonic acid to form leukotrienes and the normal functioning of proteins in fluid balance and lipoprotein transport.
PEM is fairly common worldwide in both children and adults and accounts for 6 million deaths annually. In the industrialized world, PEM is predominantly seen in hospitals, is associated with disease, or is often found in the elderly.
See also[edit]
Food portal
Azotorrhea
Biological value
Bodybuilding supplement
Leaf protein concentrate
Low-protein diet
Ninja diet
Protein bar
Single-cell protein
List of proteins in the human body | biology | 777496 | https://da.wikipedia.org/wiki/Proteinpulver | Proteinpulver | Proteinpulver er pulver med højt indhold af protein til ernæring. Protein bliver typisk associeret med fitness/bodybuilding industrien, men har de senere år vundet indflydelse i ganske normale slankekure. Protein er opbygget af aminosyrer og proteinpulver er ingen undtagelse. Proteinpulver kan være lavet på mange forskellige råvarer, men den typiske er valleprotein som stammer fra mælk. Det skyldes mælkens fordelagtige aminosyresammensætning og dertil optagelseshastigheden i kroppen.
Brugen af protein
Ved større mængde af vægttræning har kroppen brug for mere indtag af protein end normalt. Som tommelfingerregel og hvis formålet er øget muskelmasse, har både mænd og kvinder brug for 1,2 - 1,7 g protein per kg kropsvægt. Vejer en mand 75 kg og en kvinde 55 kg, kan følgende formel fx bruges:
1,7x75 kg = cirka 127,5 gram protein dagligt.
1,2x55 kg = cirka 71,6 gram protein dagligt.
Når producenterne forsøger, at sammensætte det bedste kosttilskud har de ofte for øje, at proteinpulveret skal have et højt indhold af EAA (Essential Amino Acids = Essentielle Aminosyrer) og dertil et højt indhold af BCAA (Branched Chained Amino Acids = Forgrenede Aminosyrer). Det siger sig selv, at de essentielle aminosyrer ikke kan produceres i kroppen, hvilket forklarer hvorfor de er essentielle. Forgrenede aminosyrer har i flere studier vist sig, at være meget fordelagtige aminosyrer som i høj grad påvirker proteinsyntesen, hvilket øger protein produktionen i kroppen og på den måde påvirker det overall turnover af protein (muskel væv) i kroppen.
Proteinpulver bliver også produceret af ærter, ris, soyabønner, oksekød, hamp og æg. Mest populær er dog valleproteinpulver, som kommer fra mælk, da den smager bedst og samtidig har den optimale aminosyreprofil til opbygning af muskelmasse. Laktoseintolerante må dog ty til alternative for kilder, for at undgå mælken og laktosen fra valle proteinpulveret. Dog kan valleprotein-isolat ofte benyttes af laktoseintolerante, da næsten alt sukkeret fra mælken er filtreret fra.
Proteinpulver bruges også som ingrediens i en række andre produkter indenfor fitnessindustrien, herunder proteinbarer, proteinshakes og weight gainer. En stor mængde af danskere indtager for store mængder protein, og derfor anvender kroppen proteinen som energikilde i stedet for byggesten til kroppen celler.
Kilder
Kosttilskud | danish | 0.345951 |
protein_in_food/Protein.txt |
Proteins are large biomolecules and macromolecules that comprise one or more long chains of amino acid residues. Proteins perform a vast array of functions within organisms, including catalysing metabolic reactions, DNA replication, responding to stimuli, providing structure to cells and organisms, and transporting molecules from one location to another. Proteins differ from one another primarily in their sequence of amino acids, which is dictated by the nucleotide sequence of their genes, and which usually results in protein folding into a specific 3D structure that determines its activity.
A linear chain of amino acid residues is called a polypeptide. A protein contains at least one long polypeptide. Short polypeptides, containing less than 20–30 residues, are rarely considered to be proteins and are commonly called peptides. The individual amino acid residues are bonded together by peptide bonds and adjacent amino acid residues. The sequence of amino acid residues in a protein is defined by the sequence of a gene, which is encoded in the genetic code. In general, the genetic code specifies 20 standard amino acids; but in certain organisms the genetic code can include selenocysteine and—in certain archaea—pyrrolysine. Shortly after or even during synthesis, the residues in a protein are often chemically modified by post-translational modification, which alters the physical and chemical properties, folding, stability, activity, and ultimately, the function of the proteins. Some proteins have non-peptide groups attached, which can be called prosthetic groups or cofactors. Proteins can also work together to achieve a particular function, and they often associate to form stable protein complexes.
Once formed, proteins only exist for a certain period and are then degraded and recycled by the cell's machinery through the process of protein turnover. A protein's lifespan is measured in terms of its half-life and covers a wide range. They can exist for minutes or years with an average lifespan of 1–2 days in mammalian cells. Abnormal or misfolded proteins are degraded more rapidly either due to being targeted for destruction or due to being unstable.
Like other biological macromolecules such as polysaccharides and nucleic acids, proteins are essential parts of organisms and participate in virtually every process within cells. Many proteins are enzymes that catalyse biochemical reactions and are vital to metabolism. Proteins also have structural or mechanical functions, such as actin and myosin in muscle and the proteins in the cytoskeleton, which form a system of scaffolding that maintains cell shape. Other proteins are important in cell signaling, immune responses, cell adhesion, and the cell cycle. In animals, proteins are needed in the diet to provide the essential amino acids that cannot be synthesized. Digestion breaks the proteins down for metabolic use.
Proteins may be purified from other cellular components using a variety of techniques such as ultracentrifugation, precipitation, electrophoresis, and chromatography; the advent of genetic engineering has made possible a number of methods to facilitate purification. Methods commonly used to study protein structure and function include immunohistochemistry, site-directed mutagenesis, X-ray crystallography, nuclear magnetic resonance and mass spectrometry.
History and etymology
Further information: History of molecular biology
Proteins were recognized as a distinct class of biological molecules in the eighteenth century by Antoine Fourcroy and others, distinguished by the molecules' ability to coagulate or flocculate under treatments with heat or acid. Noted examples at the time included albumin from egg whites, blood serum albumin, fibrin, and wheat gluten.
Proteins were first described by the Dutch chemist Gerardus Johannes Mulder and named by the Swedish chemist Jöns Jacob Berzelius in 1838. Mulder carried out elemental analysis of common proteins and found that nearly all proteins had the same empirical formula, C400H620N100O120P1S1. He came to the erroneous conclusion that they might be composed of a single type of (very large) molecule. The term "protein" to describe these molecules was proposed by Mulder's associate Berzelius; protein is derived from the Greek word πρώτειος (proteios), meaning "primary", "in the lead", or "standing in front", + -in. Mulder went on to identify the products of protein degradation such as the amino acid leucine for which he found a (nearly correct) molecular weight of 131 Da. Prior to "protein", other names were used, like "albumins" or "albuminous materials" (Eiweisskörper, in German).
Early nutritional scientists such as the German Carl von Voit believed that protein was the most important nutrient for maintaining the structure of the body, because it was generally believed that "flesh makes flesh." Karl Heinrich Ritthausen extended known protein forms with the identification of glutamic acid. At the Connecticut Agricultural Experiment Station a detailed review of the vegetable proteins was compiled by Thomas Burr Osborne. Working with Lafayette Mendel and applying Liebig's law of the minimum in feeding laboratory rats, the nutritionally essential amino acids were established. The work was continued and communicated by William Cumming Rose. The understanding of proteins as polypeptides came through the work of Franz Hofmeister and Hermann Emil Fischer in 1902. The central role of proteins as enzymes in living organisms was not fully appreciated until 1926, when James B. Sumner showed that the enzyme urease was in fact a protein.
The difficulty in purifying proteins in large quantities made them very difficult for early protein biochemists to study. Hence, early studies focused on proteins that could be purified in large quantities, e.g., those of blood, egg white, various toxins, and digestive/metabolic enzymes obtained from slaughterhouses. In the 1950s, the Armour Hot Dog Co. purified 1 kg of pure bovine pancreatic ribonuclease A and made it freely available to scientists; this gesture helped ribonuclease A become a major target for biochemical study for the following decades.
Linus Pauling is credited with the successful prediction of regular protein secondary structures based on hydrogen bonding, an idea first put forth by William Astbury in 1933. Later work by Walter Kauzmann on denaturation, based partly on previous studies by Kaj Linderstrøm-Lang, contributed an understanding of protein folding and structure mediated by hydrophobic interactions.
The first protein to be sequenced was insulin, by Frederick Sanger, in 1949. Sanger correctly determined the amino acid sequence of insulin, thus conclusively demonstrating that proteins consisted of linear polymers of amino acids rather than branched chains, colloids, or cyclols. He won the Nobel Prize for this achievement in 1958.
John Kendrew with model of myoglobin in progress
With the development of X-ray crystallography, it became possible to sequence protein structures. The first protein structures to be solved were hemoglobin by Max Perutz and myoglobin by John Kendrew, in 1958. The use of computers and increasing computing power also supported the sequencing of complex proteins. In 1999, Roger Kornberg succeeded in sequencing the highly complex structure of RNA polymerase using high intensity X-rays from synchrotrons.
Since then, cryo-electron microscopy (cryo-EM) of large macromolecular assemblies has been developed. Cryo-EM uses protein samples that are frozen rather than crystals, and beams of electrons rather than x-rays. It causes less damage to the sample, allowing scientists to obtain more information and analyze larger structures. Computational protein structure prediction of small protein domains has also helped researchers to approach atomic-level resolution of protein structures.
As of 2017, the Protein Data Bank has over 126,060 atomic-resolution structures of proteins.
Number of proteins encoded in genomes
The number of proteins encoded in a genome roughly corresponds to the number of genes (although there may be a significant number of genes that encode RNA of protein, e.g. ribosomal RNAs). Viruses typically encode a few to a few hundred proteins, archaea and bacteria a few hundred to a few thousand, while eukaryotes typically encode a few thousand up to tens of thousands of proteins (see genome size for a list of examples).
Classification
Main articles: Protein family, Gene Ontology, and Enzyme Commission number
Proteins are primarily classified by sequence and structure, although other classifications are commonly used. Especially for enzymes the EC number system provides a functional classification scheme. Similarly, the gene ontology classifies both genes and proteins by their biological and biochemical function, but also by their intracellular location.
Sequence similarity is used to classify proteins both in terms of evolutionary and functional similarity. This may use either whole proteins or protein domains, especially in multi-domain proteins. Protein domains allow protein classification by a combination of sequence, structure and function, and thy can be combined in many different ways. In an early study of 170,000 proteins, about two-thirds were assigned at least one domain, with larger proteins containing more domains (e.g. proteins larger than 600 amino acids having an average of more than 5 domains).
Biochemistry
Chemical structure of the peptide bond (bottom) and the three-dimensional structure of a peptide bond between an alanine and an adjacent amino acid (top/inset). The bond itself is made of the CHON elements.
Resonance structures of the peptide bond that links individual amino acids to form a protein polymer
Main articles: Biochemistry, Amino acid, and Peptide bond
Most proteins consist of linear polymers built from series of up to 20 different L-α- amino acids. All proteinogenic amino acids possess common structural features, including an α-carbon to which an amino group, a carboxyl group, and a variable side chain are bonded. Only proline differs from this basic structure as it contains an unusual ring to the N-end amine group, which forces the CO–NH amide moiety into a fixed conformation. The side chains of the standard amino acids, detailed in the list of standard amino acids, have a great variety of chemical structures and properties; it is the combined effect of all of the amino acid side chains in a protein that ultimately determines its three-dimensional structure and its chemical reactivity.
The amino acids in a polypeptide chain are linked by peptide bonds. Once linked in the protein chain, an individual amino acid is called a residue, and the linked series of carbon, nitrogen, and oxygen atoms are known as the main chain or protein backbone.
The peptide bond has two resonance forms that contribute some double-bond character and inhibit rotation around its axis, so that the alpha carbons are roughly coplanar. The other two dihedral angles in the peptide bond determine the local shape assumed by the protein backbone. The end with a free amino group is known as the N-terminus or amino terminus, whereas the end of the protein with a free carboxyl group is known as the C-terminus or carboxy terminus (the sequence of the protein is written from N-terminus to C-terminus, from left to right).
The words protein, polypeptide, and peptide are a little ambiguous and can overlap in meaning. Protein is generally used to refer to the complete biological molecule in a stable conformation, whereas peptide is generally reserved for a short amino acid oligomers often lacking a stable 3D structure. But the boundary between the two is not well defined and usually lies near 20–30 residues. Polypeptide can refer to any single linear chain of amino acids, usually regardless of length, but often implies an absence of a defined conformation.
Interactions
Proteins can interact with many types of molecules, including with other proteins, with lipids, with carbohydrates, and with DNA.
Abundance in cells
It has been estimated that average-sized bacteria contain about 2 million proteins per cell (e.g. E. coli and Staphylococcus aureus). Smaller bacteria, such as Mycoplasma or spirochetes contain fewer molecules, on the order of 50,000 to 1 million. By contrast, eukaryotic cells are larger and thus contain much more protein. For instance, yeast cells have been estimated to contain about 50 million proteins and human cells on the order of 1 to 3 billion. The concentration of individual protein copies ranges from a few molecules per cell up to 20 million. Not all genes coding proteins are expressed in most cells and their number depends on, for example, cell type and external stimuli. For instance, of the 20,000 or so proteins encoded by the human genome, only 6,000 are detected in lymphoblastoid cells.
Synthesis
Biosynthesis
A ribosome produces a protein using mRNA as template
The DNA sequence of a gene encodes the amino acid sequence of a protein
Main article: Protein biosynthesis
Proteins are assembled from amino acids using information encoded in genes. Each protein has its own unique amino acid sequence that is specified by the nucleotide sequence of the gene encoding this protein. The genetic code is a set of three-nucleotide sets called codons and each three-nucleotide combination designates an amino acid, for example AUG (adenine–uracil–guanine) is the code for methionine. Because DNA contains four nucleotides, the total number of possible codons is 64; hence, there is some redundancy in the genetic code, with some amino acids specified by more than one codon. Genes encoded in DNA are first transcribed into pre-messenger RNA (mRNA) by proteins such as RNA polymerase. Most organisms then process the pre-mRNA (also known as a primary transcript) using various forms of post-transcriptional modification to form the mature mRNA, which is then used as a template for protein synthesis by the ribosome. In prokaryotes the mRNA may either be used as soon as it is produced, or be bound by a ribosome after having moved away from the nucleoid. In contrast, eukaryotes make mRNA in the cell nucleus and then translocate it across the nuclear membrane into the cytoplasm, where protein synthesis then takes place. The rate of protein synthesis is higher in prokaryotes than eukaryotes and can reach up to 20 amino acids per second.
The process of synthesizing a protein from an mRNA template is known as translation. The mRNA is loaded onto the ribosome and is read three nucleotides at a time by matching each codon to its base pairing anticodon located on a transfer RNA molecule, which carries the amino acid corresponding to the codon it recognizes. The enzyme aminoacyl tRNA synthetase "charges" the tRNA molecules with the correct amino acids. The growing polypeptide is often termed the nascent chain. Proteins are always biosynthesized from N-terminus to C-terminus.
The size of a synthesized protein can be measured by the number of amino acids it contains and by its total molecular mass, which is normally reported in units of daltons (synonymous with atomic mass units), or the derivative unit kilodalton (kDa). The average size of a protein increases from Archaea to Bacteria to Eukaryote (283, 311, 438 residues and 31, 34, 49 kDa respectively) due to a bigger number of protein domains constituting proteins in higher organisms. For instance, yeast proteins are on average 466 amino acids long and 53 kDa in mass. The largest known proteins are the titins, a component of the muscle sarcomere, with a molecular mass of almost 3,000 kDa and a total length of almost 27,000 amino acids.
Chemical synthesis
Main article: Peptide synthesis
Short proteins can also be synthesized chemically by a family of methods known as peptide synthesis, which rely on organic synthesis techniques such as chemical ligation to produce peptides in high yield. Chemical synthesis allows for the introduction of non-natural amino acids into polypeptide chains, such as attachment of fluorescent probes to amino acid side chains. These methods are useful in laboratory biochemistry and cell biology, though generally not for commercial applications. Chemical synthesis is inefficient for polypeptides longer than about 300 amino acids, and the synthesized proteins may not readily assume their native tertiary structure. Most chemical synthesis methods proceed from C-terminus to N-terminus, opposite the biological reaction.
Structure
The crystal structure of the chaperonin, a huge protein complex. A single protein subunit is highlighted. Chaperonins assist protein folding.
Three possible representations of the three-dimensional structure of the protein triose phosphate isomerase. Left: All-atom representation colored by atom type. Middle: Simplified representation illustrating the backbone conformation, colored by secondary structure. Right: Solvent-accessible surface representation colored by residue type (acidic residues red, basic residues blue, polar residues green, nonpolar residues white).
Main article: Protein structure
Further information: Protein structure prediction
Most proteins fold into unique 3D structures. The shape into which a protein naturally folds is known as its native conformation. Although many proteins can fold unassisted, simply through the chemical properties of their amino acids, others require the aid of molecular chaperones to fold into their native states. Biochemists often refer to four distinct aspects of a protein's structure:
Primary structure: the amino acid sequence. A protein is a polyamide.
Secondary structure: regularly repeating local structures stabilized by hydrogen bonds. The most common examples are the α-helix, β-sheet and turns. Because secondary structures are local, many regions of different secondary structure can be present in the same protein molecule.
Tertiary structure: the overall shape of a single protein molecule; the spatial relationship of the secondary structures to one another. Tertiary structure is generally stabilized by nonlocal interactions, most commonly the formation of a hydrophobic core, but also through salt bridges, hydrogen bonds, disulfide bonds, and even post-translational modifications. The term "tertiary structure" is often used as synonymous with the term fold. The tertiary structure is what controls the basic function of the protein.
Quaternary structure: the structure formed by several protein molecules (polypeptide chains), usually called protein subunits in this context, which function as a single protein complex.
Quinary structure: the signatures of protein surface that organize the crowded cellular interior. Quinary structure is dependent on transient, yet essential, macromolecular interactions that occur inside living cells.
Proteins are not entirely rigid molecules. In addition to these levels of structure, proteins may shift between several related structures while they perform their functions. In the context of these functional rearrangements, these tertiary or quaternary structures are usually referred to as "conformations", and transitions between them are called conformational changes. Such changes are often induced by the binding of a substrate molecule to an enzyme's active site, or the physical region of the protein that participates in chemical catalysis. In solution, proteins also undergo variation in structure through thermal vibration and the collision with other molecules.
Molecular surface of several proteins showing their comparative sizes. From left to right are: immunoglobulin G (IgG, an antibody), hemoglobin, insulin (a hormone), adenylate kinase (an enzyme), and glutamine synthetase (an enzyme).
Proteins can be informally divided into three main classes, which correlate with typical tertiary structures: globular proteins, fibrous proteins, and membrane proteins. Almost all globular proteins are soluble and many are enzymes. Fibrous proteins are often structural, such as collagen, the major component of connective tissue, or keratin, the protein component of hair and nails. Membrane proteins often serve as receptors or provide channels for polar or charged molecules to pass through the cell membrane.
A special case of intramolecular hydrogen bonds within proteins, poorly shielded from water attack and hence promoting their own dehydration, are called dehydrons.
Protein domains
Main article: Protein domain
Many proteins are composed of several protein domains, i.e. segments of a protein that fold into distinct structural units. Domains usually also have specific functions, such as enzymatic activities (e.g. kinase) or they serve as binding modules (e.g. the SH3 domain binds to proline-rich sequences in other proteins).
Sequence motif
Short amino acid sequences within proteins often act as recognition sites for other proteins. For instance, SH3 domains typically bind to short PxxP motifs (i.e. 2 prolines [P], separated by two unspecified amino acids [x], although the surrounding amino acids may determine the exact binding specificity). Many such motifs has been collected in the Eukaryotic Linear Motif (ELM) database.
Protein topology
Topology of a protein describes the entanglement of the backbone and the arrangement of contacts within the folded chain. Two theoretical frameworks of knot theory and Circuit topology have been applied to characterise protein topology. Being able to describe protein topology opens up new pathways for protein engineering and pharmaceutical development, and adds to our understanding of protein misfolding diseases such as neuromuscular disorders and cancer.
Cellular functions
Proteins are the chief actors within the cell, said to be carrying out the duties specified by the information encoded in genes. With the exception of certain types of RNA, most other biological molecules are relatively inert elements upon which proteins act. Proteins make up half the dry weight of an Escherichia coli cell, whereas other macromolecules such as DNA and RNA make up only 3% and 20%, respectively. The set of proteins expressed in a particular cell or cell type is known as its proteome.
The enzyme hexokinase is shown as a conventional ball-and-stick molecular model. To scale in the top right-hand corner are two of its substrates, ATP and glucose.
The chief characteristic of proteins that also allows their diverse set of functions is their ability to bind other molecules specifically and tightly. The region of the protein responsible for binding another molecule is known as the binding site and is often a depression or "pocket" on the molecular surface. This binding ability is mediated by the tertiary structure of the protein, which defines the binding site pocket, and by the chemical properties of the surrounding amino acids' side chains. Protein binding can be extraordinarily tight and specific; for example, the ribonuclease inhibitor protein binds to human angiogenin with a sub-femtomolar dissociation constant (<10 M) but does not bind at all to its amphibian homolog onconase (>1 M). Extremely minor chemical changes such as the addition of a single methyl group to a binding partner can sometimes suffice to nearly eliminate binding; for example, the aminoacyl tRNA synthetase specific to the amino acid valine discriminates against the very similar side chain of the amino acid isoleucine.
Proteins can bind to other proteins as well as to small-molecule substrates. When proteins bind specifically to other copies of the same molecule, they can oligomerize to form fibrils; this process occurs often in structural proteins that consist of globular monomers that self-associate to form rigid fibers. Protein–protein interactions also regulate enzymatic activity, control progression through the cell cycle, and allow the assembly of large protein complexes that carry out many closely related reactions with a common biological function. Proteins can also bind to, or even be integrated into, cell membranes. The ability of binding partners to induce conformational changes in proteins allows the construction of enormously complex signaling networks.
As interactions between proteins are reversible, and depend heavily on the availability of different groups of partner proteins to form aggregates that are capable to carry out discrete sets of function, study of the interactions between specific proteins is a key to understand important aspects of cellular function, and ultimately the properties that distinguish particular cell types.
Enzymes
Main article: Enzyme
The best-known role of proteins in the cell is as enzymes, which catalyse chemical reactions. Enzymes are usually highly specific and accelerate only one or a few chemical reactions. Enzymes carry out most of the reactions involved in metabolism, as well as manipulating DNA in processes such as DNA replication, DNA repair, and transcription. Some enzymes act on other proteins to add or remove chemical groups in a process known as posttranslational modification. About 4,000 reactions are known to be catalysed by enzymes. The rate acceleration conferred by enzymatic catalysis is often enormous—as much as 10-fold increase in rate over the uncatalysed reaction in the case of orotate decarboxylase (78 million years without the enzyme, 18 milliseconds with the enzyme).
The molecules bound and acted upon by enzymes are called substrates. Although enzymes can consist of hundreds of amino acids, it is usually only a small fraction of the residues that come in contact with the substrate, and an even smaller fraction—three to four residues on average—that are directly involved in catalysis. The region of the enzyme that binds the substrate and contains the catalytic residues is known as the active site.
Dirigent proteins are members of a class of proteins that dictate the stereochemistry of a compound synthesized by other enzymes.
Cell signaling and ligand binding
See also: Glycan-protein interactions
Ribbon diagram of a mouse antibody against cholera that binds a carbohydrate antigen
Many proteins are involved in the process of cell signaling and signal transduction. Some proteins, such as insulin, are extracellular proteins that transmit a signal from the cell in which they were synthesized to other cells in distant tissues. Others are membrane proteins that act as receptors whose main function is to bind a signaling molecule and induce a biochemical response in the cell. Many receptors have a binding site exposed on the cell surface and an effector domain within the cell, which may have enzymatic activity or may undergo a conformational change detected by other proteins within the cell.
Antibodies are protein components of an adaptive immune system whose main function is to bind antigens, or foreign substances in the body, and target them for destruction. Antibodies can be secreted into the extracellular environment or anchored in the membranes of specialized B cells known as plasma cells. Whereas enzymes are limited in their binding affinity for their substrates by the necessity of conducting their reaction, antibodies have no such constraints. An antibody's binding affinity to its target is extraordinarily high.
Many ligand transport proteins bind particular small biomolecules and transport them to other locations in the body of a multicellular organism. These proteins must have a high binding affinity when their ligand is present in high concentrations, but must also release the ligand when it is present at low concentrations in the target tissues. The canonical example of a ligand-binding protein is haemoglobin, which transports oxygen from the lungs to other organs and tissues in all vertebrates and has close homologs in every biological kingdom. Lectins are sugar-binding proteins which are highly specific for their sugar moieties. Lectins typically play a role in biological recognition phenomena involving cells and proteins. Receptors and hormones are highly specific binding proteins.
Transmembrane proteins can also serve as ligand transport proteins that alter the permeability of the cell membrane to small molecules and ions. The membrane alone has a hydrophobic core through which polar or charged molecules cannot diffuse. Membrane proteins contain internal channels that allow such molecules to enter and exit the cell. Many ion channel proteins are specialized to select for only a particular ion; for example, potassium and sodium channels often discriminate for only one of the two ions.
Structural proteins
Structural proteins confer stiffness and rigidity to otherwise-fluid biological components. Most structural proteins are fibrous proteins; for example, collagen and elastin are critical components of connective tissue such as cartilage, and keratin is found in hard or filamentous structures such as hair, nails, feathers, hooves, and some animal shells. Some globular proteins can also play structural functions, for example, actin and tubulin are globular and soluble as monomers, but polymerize to form long, stiff fibers that make up the cytoskeleton, which allows the cell to maintain its shape and size.
Other proteins that serve structural functions are motor proteins such as myosin, kinesin, and dynein, which are capable of generating mechanical forces. These proteins are crucial for cellular motility of single celled organisms and the sperm of many multicellular organisms which reproduce sexually. They also generate the forces exerted by contracting muscles and play essential roles in intracellular transport.
Protein evolution
Main article: Molecular evolution
A key question in molecular biology is how proteins evolve, i.e. how can mutations (or rather changes in amino acid sequence) lead to new structures and functions? Most amino acids in a protein can be changed without disrupting activity or function, as can be seen from numerous homologous proteins across species (as collected in specialized databases for protein families, e.g. PFAM). In order to prevent dramatic consequences of mutations, a gene may be duplicated before it can mutate freely. However, this can also lead to complete loss of gene function and thus pseudo-genes. More commonly, single amino acid changes have limited consequences although some can change protein function substantially, especially in enzymes. For instance, many enzymes can change their substrate specificity by one or a few mutations. Changes in substrate specificity are facilitated by substrate promiscuity, i.e. the ability of many enzymes to bind and process multiple substrates. When mutations occur, the specificity of an enzyme can increase (or decrease) and thus its enzymatic activity. Thus, bacteria (or other organisms) can adapt to different food sources, including unnatural substrates such as plastic.
Methods of study
Main article: Protein methods
The activities and structures of proteins may be examined in vitro, in vivo, and in silico. In vitro studies of purified proteins in controlled environments are useful for learning how a protein carries out its function: for example, enzyme kinetics studies explore the chemical mechanism of an enzyme's catalytic activity and its relative affinity for various possible substrate molecules. By contrast, in vivo experiments can provide information about the physiological role of a protein in the context of a cell or even a whole organism. In silico studies use computational methods to study proteins.
Protein purification
Main article: Protein purification
To perform in vitro analysis, a protein must be purified away from other cellular components. This process usually begins with cell lysis, in which a cell's membrane is disrupted and its internal contents released into a solution known as a crude lysate. The resulting mixture can be purified using ultracentrifugation, which fractionates the various cellular components into fractions containing soluble proteins; membrane lipids and proteins; cellular organelles, and nucleic acids. Precipitation by a method known as salting out can concentrate the proteins from this lysate. Various types of chromatography are then used to isolate the protein or proteins of interest based on properties such as molecular weight, net charge and binding affinity. The level of purification can be monitored using various types of gel electrophoresis if the desired protein's molecular weight and isoelectric point are known, by spectroscopy if the protein has distinguishable spectroscopic features, or by enzyme assays if the protein has enzymatic activity. Additionally, proteins can be isolated according to their charge using electrofocusing.
For natural proteins, a series of purification steps may be necessary to obtain protein sufficiently pure for laboratory applications. To simplify this process, genetic engineering is often used to add chemical features to proteins that make them easier to purify without affecting their structure or activity. Here, a "tag" consisting of a specific amino acid sequence, often a series of histidine residues (a "His-tag"), is attached to one terminus of the protein. As a result, when the lysate is passed over a chromatography column containing nickel, the histidine residues ligate the nickel and attach to the column while the untagged components of the lysate pass unimpeded. A number of different tags have been developed to help researchers purify specific proteins from complex mixtures.
Cellular localization
Proteins in different cellular compartments and structures tagged with green fluorescent protein (here, white)
The study of proteins in vivo is often concerned with the synthesis and localization of the protein within the cell. Although many intracellular proteins are synthesized in the cytoplasm and membrane-bound or secreted proteins in the endoplasmic reticulum, the specifics of how proteins are targeted to specific organelles or cellular structures is often unclear. A useful technique for assessing cellular localization uses genetic engineering to express in a cell a fusion protein or chimera consisting of the natural protein of interest linked to a "reporter" such as green fluorescent protein (GFP). The fused protein's position within the cell can then be cleanly and efficiently visualized using microscopy, as shown in the figure opposite.
Other methods for elucidating the cellular location of proteins requires the use of known compartmental markers for regions such as the ER, the Golgi, lysosomes or vacuoles, mitochondria, chloroplasts, plasma membrane, etc. With the use of fluorescently tagged versions of these markers or of antibodies to known markers, it becomes much simpler to identify the localization of a protein of interest. For example, indirect immunofluorescence will allow for fluorescence colocalization and demonstration of location. Fluorescent dyes are used to label cellular compartments for a similar purpose.
Other possibilities exist, as well. For example, immunohistochemistry usually uses an antibody to one or more proteins of interest that are conjugated to enzymes yielding either luminescent or chromogenic signals that can be compared between samples, allowing for localization information. Another applicable technique is cofractionation in sucrose (or other material) gradients using isopycnic centrifugation. While this technique does not prove colocalization of a compartment of known density and the protein of interest, it does increase the likelihood, and is more amenable to large-scale studies.
Finally, the gold-standard method of cellular localization is immunoelectron microscopy. This technique also uses an antibody to the protein of interest, along with classical electron microscopy techniques. The sample is prepared for normal electron microscopic examination, and then treated with an antibody to the protein of interest that is conjugated to an extremely electro-dense material, usually gold. This allows for the localization of both ultrastructural details as well as the protein of interest.
Through another genetic engineering application known as site-directed mutagenesis, researchers can alter the protein sequence and hence its structure, cellular localization, and susceptibility to regulation. This technique even allows the incorporation of unnatural amino acids into proteins, using modified tRNAs, and may allow the rational design of new proteins with novel properties.
Proteomics
Main article: Proteomics
The total complement of proteins present at a time in a cell or cell type is known as its proteome, and the study of such large-scale data sets defines the field of proteomics, named by analogy to the related field of genomics. Key experimental techniques in proteomics include 2D electrophoresis, which allows the separation of many proteins, mass spectrometry, which allows rapid high-throughput identification of proteins and sequencing of peptides (most often after in-gel digestion), protein microarrays, which allow the detection of the relative levels of the various proteins present in a cell, and two-hybrid screening, which allows the systematic exploration of protein–protein interactions. The total complement of biologically possible such interactions is known as the interactome. A systematic attempt to determine the structures of proteins representing every possible fold is known as structural genomics.
Structure determination
Discovering the tertiary structure of a protein, or the quaternary structure of its complexes, can provide important clues about how the protein performs its function and how it can be affected, i.e. in drug design. As proteins are too small to be seen under a light microscope, other methods have to be employed to determine their structure. Common experimental methods include X-ray crystallography and NMR spectroscopy, both of which can produce structural information at atomic resolution. However, NMR experiments are able to provide information from which a subset of distances between pairs of atoms can be estimated, and the final possible conformations for a protein are determined by solving a distance geometry problem. Dual polarisation interferometry is a quantitative analytical method for measuring the overall protein conformation and conformational changes due to interactions or other stimulus. Circular dichroism is another laboratory technique for determining internal β-sheet / α-helical composition of proteins. Cryoelectron microscopy is used to produce lower-resolution structural information about very large protein complexes, including assembled viruses; a variant known as electron crystallography can also produce high-resolution information in some cases, especially for two-dimensional crystals of membrane proteins. Solved structures are usually deposited in the Protein Data Bank (PDB), a freely available resource from which structural data about thousands of proteins can be obtained in the form of Cartesian coordinates for each atom in the protein.
Many more gene sequences are known than protein structures. Further, the set of solved structures is biased toward proteins that can be easily subjected to the conditions required in X-ray crystallography, one of the major structure determination methods. In particular, globular proteins are comparatively easy to crystallize in preparation for X-ray crystallography. Membrane proteins and large protein complexes, by contrast, are difficult to crystallize and are underrepresented in the PDB. Structural genomics initiatives have attempted to remedy these deficiencies by systematically solving representative structures of major fold classes. Protein structure prediction methods attempt to provide a means of generating a plausible structure for proteins whose structures have not been experimentally determined.
Structure prediction
Constituent amino-acids can be analyzed to predict secondary, tertiary and quaternary protein structure, in this case hemoglobin containing heme units
Main articles: Protein structure prediction and List of protein structure prediction software
Complementary to the field of structural genomics, protein structure prediction develops efficient mathematical models of proteins to computationally predict the molecular formations in theory, instead of detecting structures with laboratory observation. The most successful type of structure prediction, known as homology modeling, relies on the existence of a "template" structure with sequence similarity to the protein being modeled; structural genomics' goal is to provide sufficient representation in solved structures to model most of those that remain. Although producing accurate models remains a challenge when only distantly related template structures are available, it has been suggested that sequence alignment is the bottleneck in this process, as quite accurate models can be produced if a "perfect" sequence alignment is known. Many structure prediction methods have served to inform the emerging field of protein engineering, in which novel protein folds have already been designed. Also proteins (in eukaryotes ~33%) contain large unstructured but biologically functional segments and can be classified as intrinsically disordered proteins. Predicting and analysing protein disorder is, therefore, an important part of protein structure characterisation.
Bioinformatics
Main article: Bioinformatics
A vast array of computational methods have been developed to analyze the structure, function and evolution of proteins. The development of such tools has been driven by the large amount of genomic and proteomic data available for a variety of organisms, including the human genome. It is simply impossible to study all proteins experimentally, hence only a few are subjected to laboratory experiments while computational tools are used to extrapolate to similar proteins. Such homologous proteins can be efficiently identified in distantly related organisms by sequence alignment. Genome and gene sequences can be searched by a variety of tools for certain properties. Sequence profiling tools can find restriction enzyme sites, open reading frames in nucleotide sequences, and predict secondary structures. Phylogenetic trees can be constructed and evolutionary hypotheses developed using special software like ClustalW regarding the ancestry of modern organisms and the genes they express. The field of bioinformatics is now indispensable for the analysis of genes and proteins.
In silico simulation of dynamical processes
A more complex computational problem is the prediction of intermolecular interactions, such as in molecular docking, protein folding, protein–protein interaction and chemical reactivity. Mathematical models to simulate these dynamical processes involve molecular mechanics, in particular, molecular dynamics. In this regard, in silico simulations discovered the folding of small α-helical protein domains such as the villin headpiece, the HIV accessory protein and hybrid methods combining standard molecular dynamics with quantum mechanical mathematics have explored the electronic states of rhodopsins.
Beyond classical molecular dynamics, quantum dynamics methods allow the simulation of proteins in atomistic detail with an accurate description of quantum mechanical effects. Examples include the multi-layer multi-configuration time-dependent Hartree (MCTDH) method and the hierarchical equations of motion (HEOM) approach, which have been applied to plant cryptochromes and bacteria light-harvesting complexes, respectively. Both quantum and classical mechanical simulations of biological-scale systems are extremely computationally demanding, so distributed computing initiatives (for example, the Folding@home project) facilitate the molecular modeling by exploiting advances in GPU parallel processing and Monte Carlo techniques.
Chemical analysis
The total nitrogen content of organic matter is mainly formed by the amino groups in proteins. The Total Kjeldahl Nitrogen (TKN) is a measure of nitrogen widely used in the analysis of (waste) water, soil, food, feed and organic matter in general. As the name suggests, the Kjeldahl method is applied. More sensitive methods are available.
Nutrition
Further information: Protein (nutrient) and Protein quality
Most microorganisms and plants can biosynthesize all 20 standard amino acids, while animals (including humans) must obtain some of the amino acids from the diet. The amino acids that an organism cannot synthesize on its own are referred to as essential amino acids. Key enzymes that synthesize certain amino acids are not present in animals—such as aspartokinase, which catalyses the first step in the synthesis of lysine, methionine, and threonine from aspartate. If amino acids are present in the environment, microorganisms can conserve energy by taking up the amino acids from their surroundings and downregulating their biosynthetic pathways.
In animals, amino acids are obtained through the consumption of foods containing protein. Ingested proteins are then broken down into amino acids through digestion, which typically involves denaturation of the protein through exposure to acid and hydrolysis by enzymes called proteases. Some ingested amino acids are used for protein biosynthesis, while others are converted to glucose through gluconeogenesis, or fed into the citric acid cycle. This use of protein as a fuel is particularly important under starvation conditions as it allows the body's own proteins to be used to support life, particularly those found in muscle.
In animals such as dogs and cats, protein maintains the health and quality of the skin by promoting hair follicle growth and keratinization, and thus reducing the likelihood of skin problems producing malodours. Poor-quality proteins also have a role regarding gastrointestinal health, increasing the potential for flatulence and odorous compounds in dogs because when proteins reach the colon in an undigested state, they are fermented producing hydrogen sulfide gas, indole, and skatole. Dogs and cats digest animal proteins better than those from plants, but products of low-quality animal origin are poorly digested, including skin, feathers, and connective tissue.
See also
Deproteination
DNA-binding protein
Macromolecule
Index of protein-related articles
Intein
List of proteins
Proteopathy
Proteopedia
Proteolysis
Protein sequence space
Protein superfamily
| biology | 1814243 | https://no.wikipedia.org/wiki/Bakteriofag%20%CE%BB | Bakteriofag λ | Bakteriofag λ er en bakteriofag som snylter på Escherichia coli. Den er et av de mest studerte modellsystemer i molekylærbiologi og er blitt benyttet a som et verktøy for å forstå forskjellige fundamentale prinsipper i biologi, slike som genregulering og DNA-replikasjon.
λ har et symmetrisk ikosaederformet hode med en diameter på 60 nanometer og et dobbelttrådet DNA-molekyl på 48.502 basepar som genom. Den kan benytte seg av både lytisk og lysogen vekst.
λ har proteinet LamB som reseptor og binder seg til og sender DNA-et sitt gjennom denne. LamB er et protein som sitt på celleyten til E. coli og blir kodet for av en del av operonet for maltose.
Kilder
Bakteriofager | norwegian_bokmål | 0.798803 |
adults_lose_hearing/Presbycusis.txt | Presbycusis (also spelled presbyacusis, from Greek πρέσβυς presbys "old" + ἄκουσις akousis "hearing"), or age-related hearing loss, is the cumulative effect of aging on hearing. It is a progressive and irreversible bilateral symmetrical age-related sensorineural hearing loss resulting from degeneration of the cochlea or associated structures of the inner ear or auditory nerves. The hearing loss is most marked at higher frequencies. Hearing loss that accumulates with age but is caused by factors other than normal aging (nosocusis and sociocusis) is not presbycusis, although differentiating the individual effects of distinct causes of hearing loss can be difficult.
The cause of presbycusis is a combination of genetics, cumulative environmental exposures and pathophysiological changes related to aging. At present there are no preventive measures known; treatment is by hearing aid or surgical implant.
Presbycusis is the most common cause of hearing loss, affecting one out of three persons by age 65, and one out of two by age 75. Presbycusis is the second most common illness next to arthritis in aged people.
Many vertebrates such as fish, birds and amphibians do not experience presbycusis in old age as they are able to regenerate their cochlear sensory cells, whereas mammals including humans have genetically lost this regenerative ability.
Presentation[edit]
Hearing Loss with Age (Presbycusis)
Teenagers begin to lose the ability to hear high-pitched sounds. Beyond the age of 25, many adults cannot hear this 10-second audio clip at a frequency of 17.4 kHz.
Problems playing this file? See media help.
Primary symptoms:
sounds or speech becoming dull, muffled or attenuated
need for increased volume on television, radio, music and other audio sources
difficulty using the telephone
loss of directionality of sound
difficulty understanding speech, especially women and children
difficulty in speech discrimination against background noise (cocktail party effect)
Secondary symptoms:
hyperacusis, heightened sensitivity to certain volumes and frequencies of sound, resulting from "recruitment"
tinnitus, ringing, buzzing, hissing or other sounds in the ear when no external sound is present
Usually occurs after age 50, but deterioration in hearing has been found to start very early, from about the age of 18 years. The ISO standard 7029 shows expected threshold changes due purely to age for carefully screened populations (i.e. excluding those with ear disease, noise exposure etc.), based on a meta-analysis of published data. Age affects high frequencies more than low, and men more than women. One early consequence is that even young adults may lose the ability to hear very high frequency tones above 15 or 16 kHz. Despite this, age-related hearing loss may only become noticeable later in life. The effects of age can be exacerbated by exposure to environmental noise, whether at work or in leisure time (shooting, music, etc.). This is noise-induced hearing loss (NIHL) and is distinct from presbycusis. A second exacerbating factor is exposure to ototoxic drugs and chemicals.
Over time, the detection of high-pitched sounds becomes more difficult, and speech perception is affected, particularly of sibilants and fricatives. Patients typically express a decreased ability to understand speech. Once the loss has progressed to the 2–4 kHz range, there is increased difficulty understanding consonants. Both ears tend to be affected. The impact of presbycusis on communication depends on both the severity of the condition and the communication partner.
Older adults with presbycusis often exhibit associated symptoms of social isolation, depression, anxiety, frailty and cognitive decline.
The risk of having cognitive impairment increased 7 percent for every 10 dB of hearing loss at baseline. No effect of hearing aids was seen in the Lin Baltimore study.
Causes[edit]
See also: Hearing loss § Causes
The aging process has three distinct components: physiologic degeneration, extrinsic damage (nosocusis), and intrinsic damage (sociocusis). These factors are superimposed on a genetic substrate, and may be overshadowed by general age-related susceptibility to diseases and disorders.
Hearing loss is only weakly correlated with age. In preindustrial and non-industrial societies, persons retain their hearing into old age. In the Framingham cohort study, only 10% of the variability of hearing with age could be explained by age-related physiologic deterioration. Within family groups, heredity factors were dominant; across family groups, other, presumably sociocusis and nosocusis factors were dominant.
Heredity: factors like early aging of the cochlea and susceptibility of the cochlea for drug insults are genetically determined.
Oxidative stress
General inflammatory conditions
Sociocusis[edit]
Sociocusis is the condition of those who have hearing loss attributed to continuous noise exposures, unrelated to their job or occupation. This exposure to these stimuli is frequent, and are often considered common "background noises" that affect the hearing abilities of individuals. Examples of sociocusis-related stimuli are the continuous noises from traffic, home appliances, music, television, and radio. The accumulated exposure to these noises over many years can lead to a condition similar to pure presbycusis.
Nosocusis[edit]
Nosocusis factors are those that can cause hearing loss, which are not noise-based and separate from pure presbycusis. They may include:
Ototoxic drugs: Ingestion of ototoxic drugs like aspirin may hasten the process of presbycusis.
vascular degeneration
Atherosclerosis: May diminish vascularity of the cochlea, thereby reducing its oxygen supply.
Dietary habits: Increased intake of saturated fat may accelerate atherosclerotic changes in old age.
Smoking: Is postulated to accentuate atherosclerotic changes in blood vessels aggravating presbycusis.
Diabetes: May cause vasculitis and endothelial proliferation in the blood vessels of the cochlea, thereby reducing its blood supply.
Hypertension: causes potent vascular changes, like reduction in blood supply to the cochlea, thereby aggravating presbycusis.
However, a recent study found that diabetes, atherosclerosis and hypertension had no correlation to presbycusis, suggesting that these are nosocusis (acquired hearing loss) factors, not intrinsic factors.
Pathophysiology[edit]
There are four pathological phenotypes of presbycusis:
Sensory: characterised by degeneration of the organ of Corti, the sensory organ for hearing. Located within the scala media, it contains inner and outer hair cells with stereocilia. The outer hair cells play a significant role in the amplification of sound. Age-related hair cell degeneration is characterized by loss of stereocilia, shrinkage of hair cell soma, and reduction in outer hair cell mechanical properties, suggesting that functional decline in mechanotransduction and cochlear amplification precedes hair cell loss and contributes to age-related hearing loss. At the molecular level, hair cell aging is associated with key molecular processes, including transcriptional regulation, DNA damage/repair, autophagy, and inflammatory response, as well as those related to hair cell unique morphology and function.
Neural: characterised by degeneration of cells of the spiral ganglion.
Strial/metabolic: characterised by atrophy of stria vascularis in all turns of cochlea. Located in the lateral wall of the cochlea, the stria vascularis contains sodium-potassium-ATPase pumps that are responsible for producing the endolymph resting potential. As individuals age, a loss of capillaries leads to the endolymphatic potential becoming harder to maintain, which brings a decrease in cochlear potential.
Cochlear conductive: due to stiffening of the basilar membrane thus affecting its movement. This type of pathology has not been verified as contributing to presbycusis.
In addition there are two other types:
Mixed
Indeterminate
The shape of the audiogram categorizes abrupt high-frequency loss (sensory phenotype) or flat loss (strial phenotype).
The mainstay of SNHL is strial, with only about 5% of cases being sensory. This type of presbycusis is manifested by a low-frequency hearing loss, with unimpaired speech recognition.
Classically, audiograms in neural presbycusis show a moderate downward slope into higher frequencies with a gradual worsening over time. A severe loss in speech discrimination is often described, out of proportion to the threshold loss, making amplification difficult due to poor comprehension.
The audiogram associated with sensory presbycusis is thought to show a sharply sloping high-frequency loss extending beyond the speech frequency range, and clinical evaluation reveals a slow, symmetric, and bilateral progression of hearing loss.
Diagnosis[edit]
Hearing loss is classified as mild, moderate, severe or profound. Pure-tone audiometry for air conduction thresholds at 250, 500, 1000, 2000, 4000, 6000 and 8000 Hz is traditionally used to classify the degree of hearing loss in each ear. Normal hearing thresholds are considered to be 25 dB sensitivity, though it has been proposed that this threshold is too high, and that 15 dB (about half as loud) is more typical. Mild hearing loss is thresholds of 25–45 dB; moderate hearing loss is thresholds of 45–65 dB; severe hearing loss is thresholds of 65–85 dB; and profound hearing loss thresholds are greater than 85 dB.
Tinnitus occurring in only one ear should prompt the clinician to initiate further evaluation for other etiologies. In addition, the presence of a pulse-synchronous rushing sound may require additional imaging to exclude vascular disorders.
Otoscopy[edit]
Main article: Otoscopy
An examination of the external ear canal and tympanic membrane performed by a medical doctor, otolaryngologist, or audiologist using an otoscope, a visual instrument inserted into the ear. This also allows some inspection of the middle ear through the translucent tympanic membrane.
Tympanometry[edit]
Main article: Tympanometry
A test administered by a medical doctor, otolaryngologist or audiologist of the tympanic membrane and middle ear function using a tympanometer, an air-pressure/sound wave instrument inserted into the ear canal. The result is a tympanogram showing ear canal volume, middle ear pressure and eardrum compliance. Normal middle ear function (Type A tympanogram) with a hearing loss may suggest presbycusis. Type B and Type C tympanograms indicate an abnormality inside the ear and therefore may have an additional effect on the hearing.
Laboratory studies[edit]
This may include a blood or other sera test for inflammatory markers such as those for autoinflammatory diseases.
Audiometry[edit]
Main article: Audiometry
A hearing test administered by a medical doctor, otolaryngologist (ENT) or audiologist including pure tone audiometry and speech recognition may be used to determine the extent and nature of hearing loss, and distinguish presbycusis from other kinds of hearing loss. Otoacoustic emissions and evoked response testing may be used to test for audio neuropathy. The diagnosis of a sensorineural pattern hearing loss is made through audiometry, which shows a significant hearing loss without the "air-bone gap" that is characteristic of conductive hearing disturbances. In other words, air conduction is equal to bone conduction. Persons with cochlear deficits fail otoacoustic emissions testing, while persons with 8th cranial nerve (vestibulocochlear nerve) deficits fail auditory brainstem response testing.
Presbycusis audiogram[edit]
Magnetic resonance imaging (MRI)[edit]
Main article: Magnetic resonance imaging
As part of differential diagnosis, an MRI scan may be done to check for vascular anomalies, tumors, and structural problems like enlarged mastoids. MRI and other types of scan cannot directly detect or measure age-related hearing loss.
Treatment[edit]
Main article: Sensorineural hearing loss § Treatment
At present, presbycusis, being primarily sensorineural in nature, cannot be prevented, ameliorated or cured. Treatment options fall into three categories: pharmacological, surgical and management.
There are no approved or recommended pharmaceutical treatments for presbycusis.
Cochlear implant[edit]
In cases of severe or profound hearing loss, a surgical cochlear implant is possible. This is an electronic device that replaces the cochlea of the inner ear. Electrodes are typically inserted through the round window of the cochlea, into the fluid-filled scala tympani. They stimulate the peripheral axons of the primary auditory neurons, which then send information to the brain via the auditory nerve. The cochlea is tonotopically mapped in a spiral fashion, with lower frequencies localizing at the apex of the cochlea, and high frequencies at the base of the cochlea, near the oval and round windows. With age, comes a loss in distinction of frequencies, especially higher ones. The electrodes of the implant are designed to stimulate the array of nerve fibers that previously responded to different frequencies accurately. Due to spatial constraints, the cochlear implant may not be inserted all the way into the cochlear apex. It provides a different kind of sound spectrum than natural hearing, but may enable the recipient to recognize speech and environmental sounds.
Middle ear implants[edit]
These are surgically implanted hearing aids inserted onto the middle ear. These aids work by directly vibrating the ossicles, and are cosmetically favorable due to their hidden nature.
Management[edit]
Hearing aids help improve hearing of many elderly. Hearing aids can now be tuned to specific frequency ranges of hearing loss.
Aural rehabilitation for the affected person and their communication partners may reduce the impact on communication. Techniques such as squarely facing the affected person, enunciating, ensuring adequate light, minimizing noise in the environment, and using contextual cues are used to improve comprehension.
Research[edit]
Pharmaceuticals[edit]
Pharmacological treatment options are limited, and remain clinically unproven. Among these are the water-soluble coenzyme Q10 formulation, the prescription drug Tanakan, and combination antioxidant therapy.
In a study performed in 2010, it was found that the water-soluble formulation of coenzyme Q10 (CoQ10) caused a significant improvement in liminar tonal audiometry of the air and bone thresholds at 1000 Hz, 2000 Hz, 4000 Hz, and 8000 Hz.
Antioxidant therapy – age-related hearing loss was reduced in animal models with a combination agent comprising six antioxidant agents that target four sites within the oxidative pathway: L-cysteine-glutathione mixed disulfide, ribose-cysteine, NW-nitro-L-arginine methyl ester, vitamin B12, folate, and ascorbic acid. It is thought that these supplements attenuate the decline of cochlear structure due to prolonged oxidative stress. However, more recent studies have had conflicting results. In 2012, a study was done with CBA/J female mice. They were placed on an antioxidant-rich diet for 24 months consisting of vitamins A, C, E, L-carnitine, and α-lipoic acid. While this increased the inner ear's antioxidant capacity, the actual hearing loss was unaffected. Therefore, in this study, antioxidants were shown not to improve presbycusis mechanisms.
The effects of the pharmaceutical drug Tanakan were observed when treating tympanophonia in elderly women. Tanakan was found to decrease the intensity of tympanitis and improve speech and hearing in aged patients, giving rise to the idea of recommending treatment with it to elderly patients with presbycusis or normal tonal hearing.
AM-111, an otoprotective peptide, was shown in a chinchilla study to rescue and protect against hearing loss following impulse noise trauma. AM-111 acts as a cell-permeable inhibitor of JNK-mediated apoptosis. IP injections or local injections into membrane of the round window were given, and permanent threshold shifts (PTS) were measured three weeks after impulse noise exposure. AM-111 animals had significantly lower PTS, implicating AM-111 as a possible protective agent against JNK-mediated cochlear cell death and against permanent hearing deficits after noise trauma.
The anti-inflammatory, anti-oxidant substance Ebselen was observed to reduce hearing loss in a study done in 2007. It has been previously shown that noise trauma correlates with decreases in glutathione peroxidase (GPx) activity, which has been linked to loss of the outer hair cells. GPx1, an isoform of GPx, is predominantly expressed in stria vascularis, cochlea, spiral ligament, organ of Corti, and spiral ganglion cells. The stria vascularis displayed significant decreases in GPx1 immunoreactivity and increased swelling following noise exposure in rats. There was also significant outer hair cell loss in the cochlea within five hours of noise exposure. Administration of Ebselen before and after the noise stimulus reduced stria vascularis swelling as well as cochlear outer hair cell loss. This implicates Ebselen as a supplement for GPx1 in the outer hair cell degradation mechanism of hearing loss. This treatment is currently in active clinical trials.
A γ-secretase inhibitor of Notch signaling was shown to induce new hair cells and partially recover hearing loss. Auditory hair cell loss is permanent damage due to the inability of these cells to regenerate. Therefore, deafness due to this pathology is viewed as irreversible. Hair cell development is mediated by Notch signaling, which exerts lateral inhibition onto hair cells. Notch signaling in supporting hair cells leads to prevention of differentiation in surrounding hair cells. After identifying a potent γ-secretase inhibitor selective for stimulating differentiation in inner ear stem cells, it was administered in acoustically injured mice. The animals who received the injury and treatment displayed an increased hair cell number and stimulated hearing recovery. This suggests that γ-secretase inhibition of Notch signaling can be a potential pharmacological therapy in approaching what was previously viewed as permeant deafness.
Stem cell therapy[edit]
A fetal thymus graft, or rejuvenation of the recipient immunity by inoculation of young CD4+ T cells, also prevents presbycusis as well as up-regulation of the interleukin 1 receptor type II gene (IL1R2) in CD4+ T cells and degeneration of the spiral ganglion in Samp1 mice, a murine model of human senescence. This technology remains years or even decades away from human application.
Popular culture[edit]
See also: The Mosquito
Abilities of young people to hear high frequency tones inaudible to those over 25 or so has led to the development of technologies to disperse groups of young people around shops (The Mosquito), and development of a cell phone ringtone, Teen Buzz, for students to use in school, that older people cannot hear. In September 2006 this technique was used to make a dance track called 'Buzzin'. The track had two melodies, one that everyone could hear and one that only younger people could hear.
Animals[edit]
Many vertebrates such as fish, birds and amphibians do not experience presbycusis in old age as they are able to regenerate their cochlear sensory cells, whereas mammals including humans have genetically lost this ability. A number of laboratories worldwide are conducting comparative studies of birds and mammals that aim to find the differences in regenerative capacity, with a view to developing new treatments for human hearing problems.
See also[edit]
Presbyopia – age-related degeneration of the eyes | biology | 31458 | https://da.wikipedia.org/wiki/Auditiv%20perception | Auditiv perception | Auditiv perception betyder bredt hørelse, dvs. sansning af lyd. Ofte hentyder ordet kun til den proces, der følger efter selve sansningen. Sansningen der foregår i øret består af opfangelsen af lydbølger.
Lydperception består i fortolkning og bearbejdning af sansedata, ud fra såkaldte cues. Ud fra sansesdata foretages differentiering og lokalisering af lydkilder. Der er mange forskellige cues.
Et af de cues der hjælper ved lokalisering er interaurale forskelle i amplitude og tid. Det øre der er tættest på lydkilden rammes først og dette giver hjernen information om stedet. Samtidig falder amplituden inden den rammer det andet øre. Men er kilden lige bag ved eller foran er der ikke interaurale forskelle. Der hjælper så et andet cue: Lydbølgerne ændres når de rammer torso og hoved og herved kan hjernen skelne bølger, der kommer bagfra og bølger der kommer forfra. Denne spektrale transformation af lyden kaldes Head related transfer function.
De simpleste cues, der bruges for at adskille lydkilder fra hinanden er spatial og temporal separation, altså lydkilderne befinder sig forskellige steder, og giver lyd på forskellige tidspunkter. Andre cues er modulation, frekvens, harmonicitet og intensitet.
Se også
Akustik
Kognitionspsykologi
Psykologi | danish | 0.547476 |
adults_lose_hearing/Hearing_loss.txt | "Hearing loss is a partial or total inability to hear. Hearing loss may be present at birth or acqui(...TRUNCATED) | biology | 31458 | https://da.wikipedia.org/wiki/Auditiv%20perception | Auditiv perception | "Auditiv perception betyder bredt hørelse, dvs. sansning af lyd. Ofte hentyder ordet kun til den pr(...TRUNCATED) | danish | 0.547476 |
adults_lose_hearing/Hearing.txt | "Hearing, or auditory perception, is the ability to perceive sounds through an organ, such as an ear(...TRUNCATED) | biology | 31458 | https://da.wikipedia.org/wiki/Auditiv%20perception | Auditiv perception | "Auditiv perception betyder bredt hørelse, dvs. sansning af lyd. Ofte hentyder ordet kun til den pr(...TRUNCATED) | danish | 0.547476 |
adults_lose_hearing/High_frequency.txt | "High frequency (HF) is the ITU designation for the range of radio frequency electromagnetic waves ((...TRUNCATED) | biology | 129311 | https://no.wikipedia.org/wiki/Intervallniv%C3%A5 | Intervallnivå | "Intervallnivå er det nest høyeste av fire målenivåer. Variablenes verdier kan rangeres i forhol(...TRUNCATED) | norwegian_bokmål | 1.262329 |
adults_lose_hearing/Sound.txt | "\nIn physics, sound is a vibration that propagates as an acoustic wave through a transmission mediu(...TRUNCATED) | biology | 73380 | https://sv.wikipedia.org/wiki/Akustik | Akustik | "Akustik är läran om ljud, främst hörbart ljud. Ljud är små vibrationer och i en vidare mening(...TRUNCATED) | swedish | 0.46289 |
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