{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "c47a32d8-c857-41de-a70a-cec48046df12",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e0c6bd53-3417-44bd-b1b4-81802b37fbfc",
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('binding_moad/every.csv',header=None,skiprows=2)\n",
"df = df.rename(columns={2:'pdb',3: 'ligand_name', 4: 'ligand_valid', 5: 'affinity_quantity',\n",
" 7: 'affinity_val', 8: 'affinity_unit', 9:'smiles'})\n",
"#df = df[df['ligand_valid']!='invalid'].copy()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "e40b1ddc-9a98-4a3b-b8a6-45e3940a3ea2",
"metadata": {},
"outputs": [],
"source": [
"df['is_sep'] = df[1] == 'Family. Representative Entry is '"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "4f00a0d1-78db-4f32-9d12-5e035b70ef98",
"metadata": {},
"outputs": [],
"source": [
"df['cum_sum'] = df['is_sep'].cumsum()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "ebaeb749-656e-4b92-8dbd-2e29eefdcad5",
"metadata": {},
"outputs": [],
"source": [
"quantities = ['ki','kd','ka','k1/2','kb','ic50','ec50']"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "52c0c66c-1eb0-415b-b019-bc77419ccbd7",
"metadata": {},
"outputs": [],
"source": [
"from pint import UnitRegistry\n",
"ureg = UnitRegistry()\n",
"\n",
"def to_uM(affinity_unit):\n",
" try:\n",
" val = ureg(str(affinity_unit[0])+str(affinity_unit[1]))\n",
" return val.m_as(ureg.uM)\n",
" except Exception:\n",
" pass\n",
" \n",
" try:\n",
" val = ureg(str(affinity_unit[0])+str(affinity_unit[1]))\n",
" return 1/val.m_as(1/ureg.uM)\n",
" except Exception:\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e5b4dd41-1389-408d-bee6-6dbeefc1d5c7",
"metadata": {},
"outputs": [],
"source": [
"groupby = df.groupby('cum_sum')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "61b8276c-54fe-4989-af5f-723994e1df7e",
"metadata": {},
"outputs": [],
"source": [
"def group(df):\n",
" pdb = df[df['is_sep']]['pdb'].values\n",
" if len(pdb) > 0:\n",
" pdb = pdb[0]\n",
" df['pdb_ref'] = pdb\n",
" return df[df['ligand_valid']=='valid']\n",
"df_expand = groupby.apply(group).reset_index(drop=True)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "342c8ef3-6808-471b-baa4-f9bdc7f6e8d6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"88806"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df_expand)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "8bb2dfac-5f11-455c-9dee-3607b47b4232",
"metadata": {},
"outputs": [],
"source": [
"df_expand['affinity_uM'] = df_expand[['affinity_val','affinity_unit']].apply(to_uM,axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "b5c0fa42-b595-4b96-b2d5-57f0031427dc",
"metadata": {},
"outputs": [],
"source": [
"df_filter = df_expand[df_expand['affinity_quantity'].str.lower().isin(quantities)]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "27c4865b-5337-48e0-9be7-a913b31cfae1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"88806"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df_expand)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "f3daf4ad-0205-48c0-8c38-36aa4eb561e0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"25490"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df_filter)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "0dc39f62-5b18-4a86-9a44-17d1925da2ad",
"metadata": {},
"outputs": [],
"source": [
"df_complex = pd.read_parquet('data/moad_complex.parquet')\n",
"df_complex['name'] = df_complex['name'].str.upper()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "719d147f-75eb-4ead-a54f-4b448a62a9a0",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 24,
"id": "6d158a41-64c6-4fa2-92d5-562aa11e8924",
"metadata": {},
"outputs": [],
"source": [
"df_all = df_filter.merge(df_complex,left_on='pdb_ref',right_on='name')"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "901fe6c6-dc8c-4ce4-82c6-1fb0b718287a",
"metadata": {},
"outputs": [],
"source": [
"df_all = df_all[~df_all['affinity_val'].isnull()]"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "383f9a1c-ffc6-43da-ac5a-5bcb815be28b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>pdb</th>\n",
" <th>ligand_name</th>\n",
" <th>ligand_valid</th>\n",
" <th>affinity_quantity</th>\n",
" <th>6</th>\n",
" <th>affinity_val</th>\n",
" <th>affinity_unit</th>\n",
" <th>smiles</th>\n",
" <th>10</th>\n",
" <th>is_sep</th>\n",
" <th>cum_sum</th>\n",
" <th>pdb_ref</th>\n",
" <th>affinity_uM</th>\n",
" <th>name</th>\n",
" <th>seq</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2PA:C:613</td>\n",
" <td>valid</td>\n",
" <td>Ki</td>\n",
" <td>=</td>\n",
" <td>0.62</td>\n",
" <td>nM</td>\n",
" <td>NP(=O)(N)O</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>6H8J</td>\n",
" <td>0.000620</td>\n",
" <td>6H8J</td>\n",
" <td>NYIVPGEYRVAEGEIEINAGREKTTIRVSNTGDRPIQVGSHIHFVE...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>HAE:C:800</td>\n",
" <td>valid</td>\n",
" <td>Ki</td>\n",
" <td>=</td>\n",
" <td>2.60</td>\n",
" <td>uM</td>\n",
" <td>CC(=O)NO</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>6H8J</td>\n",
" <td>2.600000</td>\n",
" <td>6H8J</td>\n",
" <td>NYIVPGEYRVAEGEIEINAGREKTTIRVSNTGDRPIQVGSHIHFVE...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>43W:A:902</td>\n",
" <td>valid</td>\n",
" <td>ic50</td>\n",
" <td>=</td>\n",
" <td>580.00</td>\n",
" <td>nM</td>\n",
" <td>C#CCCOP(=O)(O)OP(=O)(O)O</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>4S3F</td>\n",
" <td>0.580000</td>\n",
" <td>4S3F</td>\n",
" <td>MEGMRRPTPTVYVGRVPIGGAHPIAVQSMTNTPTRDVEATTAQVLE...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0CG:A:902</td>\n",
" <td>valid</td>\n",
" <td>ic50</td>\n",
" <td>=</td>\n",
" <td>770.00</td>\n",
" <td>nM</td>\n",
" <td>C#CCOP(=O)(O)OP(=O)(O)O</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>4S3F</td>\n",
" <td>0.770000</td>\n",
" <td>4S3F</td>\n",
" <td>MEGMRRPTPTVYVGRVPIGGAHPIAVQSMTNTPTRDVEATTAQVLE...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>ADN:A:901</td>\n",
" <td>valid</td>\n",
" <td>Kd</td>\n",
" <td>=</td>\n",
" <td>15.00</td>\n",
" <td>uM</td>\n",
" <td>c1nc(c2c(n1)n(cn2)[C@H]3[C@@H]([C@@H]([C@H](O3...</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>5</td>\n",
" <td>2GL0</td>\n",
" <td>15.000000</td>\n",
" <td>2GL0</td>\n",
" <td>MTDMSIKFELIDVPIPQGTNVIIGQAHFIKTVEDLYEALVTSVPGV...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25420</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>MAN NAG:G:1</td>\n",
" <td>valid</td>\n",
" <td>Ka</td>\n",
" <td>=</td>\n",
" <td>7860.00</td>\n",
" <td>M^-1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>10499</td>\n",
" <td>2WDB</td>\n",
" <td>127.226463</td>\n",
" <td>2WDB</td>\n",
" <td>MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25421</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>MAN NAG:F:1</td>\n",
" <td>valid</td>\n",
" <td>Ka</td>\n",
" <td>=</td>\n",
" <td>7860.00</td>\n",
" <td>M^-1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>10499</td>\n",
" <td>2WDB</td>\n",
" <td>127.226463</td>\n",
" <td>2WDB</td>\n",
" <td>MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25422</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NGA NAG:F:1</td>\n",
" <td>valid</td>\n",
" <td>Ka</td>\n",
" <td>=</td>\n",
" <td>5910.00</td>\n",
" <td>M^-1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>10499</td>\n",
" <td>2WDB</td>\n",
" <td>169.204738</td>\n",
" <td>2WDB</td>\n",
" <td>MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25423</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NGA NAG:E:1</td>\n",
" <td>valid</td>\n",
" <td>Ka</td>\n",
" <td>=</td>\n",
" <td>5910.00</td>\n",
" <td>M^-1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>10499</td>\n",
" <td>2WDB</td>\n",
" <td>169.204738</td>\n",
" <td>2WDB</td>\n",
" <td>MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25424</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NGA NAG:H:1</td>\n",
" <td>valid</td>\n",
" <td>Ka</td>\n",
" <td>=</td>\n",
" <td>5910.00</td>\n",
" <td>M^-1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>10499</td>\n",
" <td>2WDB</td>\n",
" <td>169.204738</td>\n",
" <td>2WDB</td>\n",
" <td>MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>25425 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 1 pdb ligand_name ligand_valid affinity_quantity 6 \\\n",
"0 NaN NaN NaN 2PA:C:613 valid Ki = \n",
"1 NaN NaN NaN HAE:C:800 valid Ki = \n",
"2 NaN NaN NaN 43W:A:902 valid ic50 = \n",
"3 NaN NaN NaN 0CG:A:902 valid ic50 = \n",
"4 NaN NaN NaN ADN:A:901 valid Kd = \n",
"... ... ... ... ... ... ... .. \n",
"25420 NaN NaN NaN MAN NAG:G:1 valid Ka = \n",
"25421 NaN NaN NaN MAN NAG:F:1 valid Ka = \n",
"25422 NaN NaN NaN NGA NAG:F:1 valid Ka = \n",
"25423 NaN NaN NaN NGA NAG:E:1 valid Ka = \n",
"25424 NaN NaN NaN NGA NAG:H:1 valid Ka = \n",
"\n",
" affinity_val affinity_unit \\\n",
"0 0.62 nM \n",
"1 2.60 uM \n",
"2 580.00 nM \n",
"3 770.00 nM \n",
"4 15.00 uM \n",
"... ... ... \n",
"25420 7860.00 M^-1 \n",
"25421 7860.00 M^-1 \n",
"25422 5910.00 M^-1 \n",
"25423 5910.00 M^-1 \n",
"25424 5910.00 M^-1 \n",
"\n",
" smiles 10 is_sep cum_sum \\\n",
"0 NP(=O)(N)O NaN False 1 \n",
"1 CC(=O)NO NaN False 1 \n",
"2 C#CCCOP(=O)(O)OP(=O)(O)O NaN False 2 \n",
"3 C#CCOP(=O)(O)OP(=O)(O)O NaN False 2 \n",
"4 c1nc(c2c(n1)n(cn2)[C@H]3[C@@H]([C@@H]([C@H](O3... NaN False 5 \n",
"... ... .. ... ... \n",
"25420 NaN NaN False 10499 \n",
"25421 NaN NaN False 10499 \n",
"25422 NaN NaN False 10499 \n",
"25423 NaN NaN False 10499 \n",
"25424 NaN NaN False 10499 \n",
"\n",
" pdb_ref affinity_uM name \\\n",
"0 6H8J 0.000620 6H8J \n",
"1 6H8J 2.600000 6H8J \n",
"2 4S3F 0.580000 4S3F \n",
"3 4S3F 0.770000 4S3F \n",
"4 2GL0 15.000000 2GL0 \n",
"... ... ... ... \n",
"25420 2WDB 127.226463 2WDB \n",
"25421 2WDB 127.226463 2WDB \n",
"25422 2WDB 169.204738 2WDB \n",
"25423 2WDB 169.204738 2WDB \n",
"25424 2WDB 169.204738 2WDB \n",
"\n",
" seq \n",
"0 NYIVPGEYRVAEGEIEINAGREKTTIRVSNTGDRPIQVGSHIHFVE... \n",
"1 NYIVPGEYRVAEGEIEINAGREKTTIRVSNTGDRPIQVGSHIHFVE... \n",
"2 MEGMRRPTPTVYVGRVPIGGAHPIAVQSMTNTPTRDVEATTAQVLE... \n",
"3 MEGMRRPTPTVYVGRVPIGGAHPIAVQSMTNTPTRDVEATTAQVLE... \n",
"4 MTDMSIKFELIDVPIPQGTNVIIGQAHFIKTVEDLYEALVTSVPGV... \n",
"... ... \n",
"25420 MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG... \n",
"25421 MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG... \n",
"25422 MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG... \n",
"25423 MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG... \n",
"25424 MGSSHHHHHHSSGLVPRGSHMASNPSLIRSESWQVYEGNEANLLDG... \n",
"\n",
"[25425 rows x 17 columns]"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_all"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "bebc962b-10f7-478c-8e23-e2d3722e875c",
"metadata": {},
"outputs": [],
"source": [
"df_all[['pdb','ligand_name','smiles','name','affinity_uM','seq']].to_parquet('data/moad.parquet')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "49a160d6-4599-488a-ba02-a65a79535f38",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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"display_name": "Python 3",
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"language_info": {
"codemirror_mode": {
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