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BALM-benchmark

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Tags:
chemistry
deep learning
protein-ligand binding affinity
biology
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BALM-benchmark / README.md
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metadata
dataset_info:
  - config_name: BindingDB_filtered
    features:
      - name: Index
        dtype: string
      - name: Drug_ID
        dtype: string
      - name: Drug
        dtype: string
      - name: Target_ID
        dtype: string
      - name: Target
        dtype: string
      - name: 'Y'
        dtype: float32
    splits:
      - name: train
        num_examples: 24700
  - config_name: CATS
    features:
      - name: Index
        dtype: string
      - name: Drug
        dtype: string
      - name: IC50
        dtype: float32
      - name: Target
        dtype: string
      - name: 'Y'
        dtype: float32
    splits:
      - name: train
        num_examples: 393
  - config_name: HIF2A
    features:
      - name: Index
        dtype: string
      - name: 'Y'
        dtype: float32
      - name: Drug
        dtype: string
      - name: Target
        dtype: string
    splits:
      - name: train
        num_examples: 37
  - config_name: HSP90
    features:
      - name: Index
        dtype: string
      - name: Drug
        dtype: string
      - name: IC50 (nM)
        dtype: float32
      - name: Target
        dtype: string
      - name: 'Y'
        dtype: float32
    splits:
      - name: train
        num_examples: 147
  - config_name: LeakyPDB
    features:
      - name: Index
        dtype: string
      - name: header
        dtype: string
      - name: smiles
        dtype: string
      - name: category
        dtype: string
      - name: seq
        dtype: string
      - name: resolution
        dtype: float32
      - name: date
        dtype: string
      - name: type
        dtype: string
      - name: new_split
        dtype: string
      - name: CL1
        dtype: bool
      - name: CL2
        dtype: bool
      - name: CL3
        dtype: bool
      - name: remove_for_balancing_val
        dtype: bool
      - name: kd/ki
        dtype: string
      - name: value
        dtype: float32
      - name: covalent
        dtype: bool
    splits:
      - name: train
        num_examples: 19443
  - config_name: MCL1
    features:
      - name: Index
        dtype: string
      - name: 'Y'
        dtype: float32
      - name: Drug
        dtype: string
      - name: Target
        dtype: string
    splits:
      - name: train
        num_examples: 25
  - config_name: Mpro
    features:
      - name: Index
        dtype: string
      - name: Drug
        dtype: string
      - name: 'Y'
        dtype: float32
      - name: Target
        dtype: string
    splits:
      - name: train
        num_examples: 2062
  - config_name: SYK
    features:
      - name: Index
        dtype: string
      - name: 'Y'
        dtype: float32
      - name: Drug
        dtype: string
      - name: Target
        dtype: string
    splits:
      - name: train
        num_examples: 44
configs:
  - config_name: BindingDB_filtered
    data_files:
      - split: train
        path: BindingDB_filtered/train/data-*
  - config_name: CATS
    data_files:
      - split: train
        path: CATS/train/data-*
  - config_name: HIF2A
    data_files:
      - split: train
        path: HIF2A/train/data-*
  - config_name: HSP90
    data_files:
      - split: train
        path: HSP90/train/data-*
  - config_name: LeakyPDB
    data_files:
      - split: train
        path: LeakyPDB/train/data-*
  - config_name: MCL1
    data_files:
      - split: train
        path: MCL1/train/data-*
  - config_name: Mpro
    data_files:
      - split: train
        path: Mpro/train/data-*
  - config_name: SYK
    data_files:
      - split: train
        path: SYK/train/data-*
license: cc-by-4.0
pretty_name: BALM-Benchmark
tags:
  - chemistry
  - biology
size_categories:
  - 10K<n<100K

Dataset Card for BALM-Benchmark

BALM-Benchmark is a comprehensive benchmark suite that combines multiple seminal binding affinity prediction datasets in one place. ...

Dataset Details

Dataset Description

Dataset Columns

  • BindingDB_filtered:
    • Index (string): Index of the ligand-target pair.
    • Drug_ID (string): Index of the ligand from the TDC.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • Target_ID (string): Index of the target protein from the TDC.
    • Target (string): Protein sequence (i.e., sequence of amino acids).
    • Y (float32): binding affinity value in pKd.
  • CATS:
    • Index (string): Index of the ligand-target pair.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • IC50 (float32): binding affinity value in IC50.
    • Target (string): Protein sequence (i.e., sequence of amino acids).
    • Y (float32): binding affinity value in pKd.
  • HIF2A:
    • Index (string): Index of the ligand-target pair.
    • Y (float32): binding affinity value in pKd.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • Target (string): Protein sequence (i.e., sequence of amino acids).
  • HSP90:
    • Index (string): Index of the ligand-target pair.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • IC50 (nM) (float32): binding affinity value in IC50.
    • Target (string): Protein sequence (i.e., sequence of amino acids).
    • Y (float32): binding affinity value in pKd.
  • LeakyPDB:
    • Index (string): Index of the ligand-target pair.
    • header (string): TBA
    • smiles (string): TBA
    • category (string): TBA
    • seq (string): TBA
    • resolution (float32): TBA
    • date (string): TBA
    • type (string): TBA
    • new_split (string): TBA
    • CL1 (bool): TBA
    • CL2 (bool): TBA
    • CL3 (bool): TBA
    • remove_for_balancing_val (bool): TBA
    • kd/ki (string): TBA
    • value (float32): TBA
    • covalent (bool): TBA
  • MCL1:
    • Index (string): Index of the ligand-target pair.
    • Y (float32): binding affinity value in pKd.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • Target (string): Protein sequence (i.e., sequence of amino acids).
  • Mpro:
    • Index (string): Index of the ligand-target pair.
    • Y (float32): binding affinity value in pKd.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • Target (string): Protein sequence (i.e., sequence of amino acids).
  • SYK:
    • Index (string): Index of the ligand-target pair.
    • Y (float32): binding affinity value in pKd.
    • Drug (string): Ligand sequence (i.e., SMILES string).
    • Target (string): Protein sequence (i.e., sequence of amino acids).

Dataset Sources

  • BindingDB_filtered:
  • CATS:
  • HIF2A:
  • HSP90:
  • LeakyPDB:
  • MCL1:
  • Mpro:
  • SYK:

Uses

BALM-Benchmark was initially created as a part of the BALM project (https://github.com/meyresearch/BALM) which fine-tunes Protein and Ligand Language Models by optimizing the distance between protein and ligand embeddings in a shared space using the cosine similarity metric that directly represents experimental binding affinity. Nevertheless, BALM-Benchmark can be used by itself, just like any other HuggingFace dataset:

from datasets import load_dataset

# For instance, you want to load SYK data. Change the second argument into SYK
syk_data = load_dataset("BALM/BALM-benchmark", "SYK", split="train")

As mentioned in the Dataset Sources, the available datasets are:

  • BindingDB_filtered
  • CATS
  • HIF2A
  • HSP90
  • LeakyPDB
  • MCL1
  • Mpro
  • SYK

Notice that all datasets only have one split (train). This is intentional such that the users can define their own splits, and can experiment with more random seeds for robustness. We highly recommend checking out different strategies for splitting the data (e.g., BindingDB) in our BALM code repository.

Citation

BibTeX:

In preparation

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