{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "834aeced-c3c5-42a0-bad1-41e009dd86ee",
   "metadata": {},
   "source": [
    "### Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "86476f6e-802a-463b-a1b0-2ae228bb92af",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9b2be11c-f4bb-4107-af49-abd78052afcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_table('../binding_datasets/pdbbind/data/plain-text-index/index/INDEX_general_PL_data.2019',skiprows=4,sep=r'\\s+',usecols=[0,4]).drop(0)\n",
    "df = df.rename(columns={'#': 'name','release': 'affinity'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "16e0fe44-96aa-4d3a-ae42-3609e895418b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from numericalunits import mL, nm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "68983ab8-bf11-4ed6-ba06-f962dbdc077e",
   "metadata": {},
   "outputs": [],
   "source": [
    "quantities = ['ki','kd','ka','k1/2','kb']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3acbca3c-9c0b-43a1-a45e-331bf153bcfa",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pint import UnitRegistry\n",
    "ureg = UnitRegistry()\n",
    "\n",
    "def to_uM(affinity):\n",
    "    val = ureg(affinity)\n",
    "    try:\n",
    "        return val.m_as(ureg.uM)\n",
    "    except Exception:\n",
    "        pass\n",
    "    \n",
    "    try:\n",
    "        return 1/val.m_as(1/ureg.uM)\n",
    "    except Exception:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "58e5748b-2cea-43ff-ab51-85a5021bd50b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['affinity_uM'] = df['affinity'].str.split('[=\\~><]').str[1].apply(to_uM)\n",
    "df['affinity_quantity'] = df['affinity'].str.split('[=\\~><]').str[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d92f0004-68c1-4487-94b9-56b4fd598de4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['affinity_quantity'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aa358835-55f3-4551-9217-e76a15de4fe8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_filter = df[df['affinity_quantity'].str.lower().isin(quantities)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d6dda488-f709-4fe7-b372-080042cf7c66",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_complex = pd.read_parquet('../binding_datasets/data/pdbbind_complex.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "df7929e3-c7fd-4e1b-a165-92f8d53b9011",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all = df_complex.merge(df_filter,on='name').drop('affinity',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4d105c42-0d11-49db-9012-52fafc9cd299",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all.to_parquet('data/pdbbind.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2955b056-26dd-45fa-8d74-f17661253a9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11099"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed3fe035-6035-4d39-b072-d12dc0a95857",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
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}