{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ecce356e-321b-441e-8a5d-a20bf72f8691",
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask.dataframe as dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "89cbcd82-4ca2-4aba-95b7-e58c0ceed770",
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = ['Ligand SMILES', 'IC50 (nM)','KEGG ID of Ligand','Ki (nM)', 'Kd (nM)','EC50 (nM)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a870d8d7-374b-4474-b9ee-305bbf9f17a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tqdm.notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e9f76b32-e8f0-47ee-b592-a91a88f4f93e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c988bc89781242ec8c8b7f8fd0b1c233",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/13 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in tqdm.notebook.tqdm(range(0,13)):\n",
    "    mycol = 'BindingDB Target Chain  Sequence.{}'.format(i)\n",
    "    allseq = ['BindingDB Target Chain  Sequence']+['BindingDB Target Chain  Sequence.{}'.format(j) for j in range(1,13)]\n",
    "    dtypes = {'BindingDB Target Chain  Sequence.{}'.format(i): 'object' for i in range(1,13)}\n",
    "    dtypes.update({'BindingDB Target Chain  Sequence': 'object',\n",
    "           'IC50 (nM)': 'object',\n",
    "           'KEGG ID of Ligand': 'object',\n",
    "           'Ki (nM)': 'object',\n",
    "           'Kd (nM)': 'object',\n",
    "           'EC50 (nM)': 'object',\n",
    "           'koff (s-1)': 'object'})\n",
    "    ddf = dd.read_csv('bindingdb/data/BindingDB_All.tsv',sep='\\t',error_bad_lines=False,blocksize=16*1024*1024,\n",
    "                      usecols=cols+allseq,\n",
    "                      dtype=dtypes)\n",
    "    ddf = ddf.reset_index()\n",
    "    ddf = ddf.rename(columns={'BindingDB Target Chain  Sequence.{}'.format(j): 'seq_{}'.format(j) for j in range(1,13)})\n",
    "    ddf = ddf.rename(columns={'BindingDB Target Chain  Sequence': 'seq_0'})\n",
    "    ddf = ddf.drop(columns={'seq_{}'.format(j) for j in range(0,13) if i != j})\n",
    "    ddf[cols+['seq_{}'.format(i)]].to_parquet('bindingdb/parquet_data/target{}'.format(i),schema='infer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "be79bbcf-0622-4d1e-8f08-a723a4167d8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "ddfs = []\n",
    "for i in range(0,13):\n",
    "    ddf = dd.read_parquet('bindingdb/parquet_data/target{}'.format(i))\n",
    "    ddf = ddf.rename(columns={'seq_{}'.format(i): 'seq'})\n",
    "    ddfs.append(ddf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "35ca09cb-6264-4526-b504-0d29236a03c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf = dd.concat(ddfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ba518a9a-0d15-47be-977b-e2dfe2511529",
   "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>Ligand SMILES</th>\n",
       "      <th>IC50 (nM)</th>\n",
       "      <th>KEGG ID of Ligand</th>\n",
       "      <th>Ki (nM)</th>\n",
       "      <th>Kd (nM)</th>\n",
       "      <th>EC50 (nM)</th>\n",
       "      <th>seq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.24</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.41</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.99</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Ligand SMILES IC50 (nM)  \\\n",
       "0      COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1      None   \n",
       "1  O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...      None   \n",
       "2  O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...      None   \n",
       "3  OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...      None   \n",
       "4  OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...      None   \n",
       "\n",
       "  KEGG ID of Ligand Ki (nM) Kd (nM) EC50 (nM)  \\\n",
       "0              None    0.24    None      None   \n",
       "1              None    0.25    None      None   \n",
       "2              None    0.41    None      None   \n",
       "3              None     0.8    None      None   \n",
       "4              None    0.99    None      None   \n",
       "\n",
       "                                                 seq  \n",
       "0  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "1  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "2  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "3  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "4  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f504d7aa-dfc1-4346-a136-8814c4b5d979",
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf.repartition(partition_size='25MB').to_parquet('bindingdb/parquet_data/all_targets',schema='infer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d7eafa69-4606-4b34-ae8f-8c6462dcb004",
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf = dd.read_parquet('../binding_affinity/bindingdb/parquet_data/all_targets')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b151868a-0cd6-405e-8401-f79918fb0b07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><strong>Dask DataFrame Structure:</strong></div>\n",
       "<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>Ligand SMILES</th>\n",
       "      <th>IC50 (nM)</th>\n",
       "      <th>KEGG ID of Ligand</th>\n",
       "      <th>Ki (nM)</th>\n",
       "      <th>Kd (nM)</th>\n",
       "      <th>EC50 (nM)</th>\n",
       "      <th>seq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=483</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: read-parquet, 483 tasks</div>"
      ],
      "text/plain": [
       "Dask DataFrame Structure:\n",
       "                Ligand SMILES IC50 (nM) KEGG ID of Ligand Ki (nM) Kd (nM) EC50 (nM)     seq\n",
       "npartitions=483                                                                            \n",
       "                       object    object            object  object  object    object  object\n",
       "                          ...       ...               ...     ...     ...       ...     ...\n",
       "...                       ...       ...               ...     ...     ...       ...     ...\n",
       "                          ...       ...               ...     ...     ...       ...     ...\n",
       "                          ...       ...               ...     ...     ...       ...     ...\n",
       "Dask Name: read-parquet, 483 tasks"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c00102b8-f4be-4ebd-8d30-7a2c7fc2d05e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf_nonnull = ddf[~ddf.seq.isnull()].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c5337e06-1e45-4180-90ed-49ac9ecdd24a",
   "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>Ligand SMILES</th>\n",
       "      <th>IC50 (nM)</th>\n",
       "      <th>KEGG ID of Ligand</th>\n",
       "      <th>Ki (nM)</th>\n",
       "      <th>Kd (nM)</th>\n",
       "      <th>EC50 (nM)</th>\n",
       "      <th>seq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.24</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.41</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.99</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Ligand SMILES IC50 (nM)  \\\n",
       "0      COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1      None   \n",
       "1  O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...      None   \n",
       "2  O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...      None   \n",
       "3  OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...      None   \n",
       "4  OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...      None   \n",
       "\n",
       "  KEGG ID of Ligand Ki (nM) Kd (nM) EC50 (nM)  \\\n",
       "0              None    0.24    None      None   \n",
       "1              None    0.25    None      None   \n",
       "2              None    0.41    None      None   \n",
       "3              None     0.8    None      None   \n",
       "4              None    0.99    None      None   \n",
       "\n",
       "                                                 seq  \n",
       "0  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "1  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "2  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "3  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  \n",
       "4  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf_nonnull.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7b423365-4989-4325-a5a5-845d852d52e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2512985"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ddf_nonnull)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "872edb84-3459-43d9-8e0e-e2a6b5d281eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pint import UnitRegistry\n",
    "import numpy as np\n",
    "import re\n",
    "ureg = UnitRegistry()\n",
    "\n",
    "def to_uM(affinities):\n",
    "    ic50, Ki, Kd, ec50 = affinities\n",
    "\n",
    "    vals = []\n",
    "        \n",
    "    try:\n",
    "        ic50 =  ureg(str(ic50)+'nM').m_as(ureg.uM)\n",
    "        vals.append(ic50)\n",
    "    except:\n",
    "        pass\n",
    "\n",
    "    try:\n",
    "        Ki = ureg(str(Ki)+'nM').m_as(ureg.uM)\n",
    "        vals.append(Ki)\n",
    "    except:\n",
    "        pass\n",
    "\n",
    "    try:\n",
    "        Kd = ureg(str(Kd)+'nM').m_as(ureg.uM)\n",
    "        vals.append(Kd)\n",
    "    except:\n",
    "        pass\n",
    "\n",
    "    try:\n",
    "        ec50 =  ureg(str(ec50)+'nM').m_as(ureg.uM)\n",
    "        vals.append(ec50)\n",
    "    except:\n",
    "        pass\n",
    "\n",
    "    if len(vals) > 0:\n",
    "        vals = np.array(vals)\n",
    "        return np.mean(vals[~np.isnan(vals)])\n",
    "    \n",
    "    return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b3cff13c-19b2-4413-a84b-d99062f516a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_nonnull = ddf_nonnull.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ca9795de-e821-4dc3-a7bf-70ade9e4c7f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Pandarallel will run on 32 workers.\n",
      "INFO: Pandarallel will use Memory file system to transfer data between the main process and workers.\n"
     ]
    }
   ],
   "source": [
    "from pandarallel import pandarallel\n",
    "pandarallel.initialize()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4356a3e2-fede-48e7-a486-343661fe0a0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_affinity = df_nonnull.copy()\n",
    "df_affinity['affinity_uM'] = df_affinity[['IC50 (nM)', 'Ki (nM)', 'Kd (nM)','EC50 (nM)']].parallel_apply(to_uM,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e91c3af8-84a5-42a2-9e25-49cb2f320b0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_affinity[~df_affinity['affinity_uM'].isnull()].to_parquet('data/bindingdb.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f602fdbe-7083-436c-9eac-9d97fbc8be67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2512985"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_affinity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "27194288-cf3e-4c30-ad55-3b0998fdf939",
   "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>Ligand SMILES</th>\n",
       "      <th>IC50 (nM)</th>\n",
       "      <th>KEGG ID of Ligand</th>\n",
       "      <th>Ki (nM)</th>\n",
       "      <th>Kd (nM)</th>\n",
       "      <th>EC50 (nM)</th>\n",
       "      <th>seq</th>\n",
       "      <th>affinity_uM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.24</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "      <td>0.00024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.25</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "      <td>0.00025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.41</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "      <td>0.00041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "      <td>0.00080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.99</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...</td>\n",
       "      <td>0.00099</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Ligand SMILES IC50 (nM)  \\\n",
       "0      COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1      None   \n",
       "1  O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(C\\C=C\\c2cn...      None   \n",
       "2  O[C@@H]1[C@@H](O)[C@@H](Cc2ccccc2)N(CC2CC2)C(=...      None   \n",
       "3  OCCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@...      None   \n",
       "4  OCCCCCN1[C@H](Cc2ccccc2)[C@H](O)[C@@H](O)[C@@H...      None   \n",
       "\n",
       "  KEGG ID of Ligand Ki (nM) Kd (nM) EC50 (nM)  \\\n",
       "0              None    0.24    None      None   \n",
       "1              None    0.25    None      None   \n",
       "2              None    0.41    None      None   \n",
       "3              None     0.8    None      None   \n",
       "4              None    0.99    None      None   \n",
       "\n",
       "                                                 seq  affinity_uM  \n",
       "0  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...      0.00024  \n",
       "1  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...      0.00025  \n",
       "2  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...      0.00041  \n",
       "3  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...      0.00080  \n",
       "4  PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...      0.00099  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_affinity.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "603fd298-0aa6-4097-b298-c55db013548c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2512985"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_affinity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d95ad9a9-d4ca-4679-8a33-235fe6e7047f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2510716"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_affinity[~df_affinity['affinity_uM'].isnull()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "372a8c60-e63c-4d6a-a144-3ab5f4d93d22",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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