02 - Feature generation - Property features.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a72d90e9",
   "metadata": {},
   "source": [
    "* import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a5755b5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv('bioavailability_data_edit01.csv')\n",
    "data = data.drop(columns='Unnamed: 0')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15d24fdd",
   "metadata": {},
   "source": [
    "# RDKit descriptors\n",
    "* add descriptor calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "549d7f4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# we generate a list of all available metrics for view as follows\n",
    "from rdkit import Chem\n",
    "from rdkit.Chem import Descriptors\n",
    "from rdkit.Chem.Descriptors import *\n",
    "\n",
    "metric_list = Descriptors._descList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "49d44ee8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['MaxEStateIndex', 'MinEStateIndex', 'MaxAbsEStateIndex', 'MinAbsEStateIndex', 'qed', 'MolWt', 'HeavyAtomMolWt', 'ExactMolWt', 'NumValenceElectrons', 'NumRadicalElectrons', 'MaxPartialCharge', 'MinPartialCharge', 'MaxAbsPartialCharge', 'MinAbsPartialCharge', 'FpDensityMorgan1', 'FpDensityMorgan2', 'FpDensityMorgan3', 'BCUT2D_MWHI', 'BCUT2D_MWLOW', 'BCUT2D_CHGHI', 'BCUT2D_CHGLO', 'BCUT2D_LOGPHI', 'BCUT2D_LOGPLOW', 'BCUT2D_MRHI', 'BCUT2D_MRLOW', 'BalabanJ', 'BertzCT', 'Chi0', 'Chi0n', 'Chi0v', 'Chi1', 'Chi1n', 'Chi1v', 'Chi2n', 'Chi2v', 'Chi3n', 'Chi3v', 'Chi4n', 'Chi4v', 'HallKierAlpha', 'Ipc', 'Kappa1', 'Kappa2', 'Kappa3', 'LabuteASA', 'PEOE_VSA1', 'PEOE_VSA10', 'PEOE_VSA11', 'PEOE_VSA12', 'PEOE_VSA13', 'PEOE_VSA14', 'PEOE_VSA2', 'PEOE_VSA3', 'PEOE_VSA4', 'PEOE_VSA5', 'PEOE_VSA6', 'PEOE_VSA7', 'PEOE_VSA8', 'PEOE_VSA9', 'SMR_VSA1', 'SMR_VSA10', 'SMR_VSA2', 'SMR_VSA3', 'SMR_VSA4', 'SMR_VSA5', 'SMR_VSA6', 'SMR_VSA7', 'SMR_VSA8', 'SMR_VSA9', 'SlogP_VSA1', 'SlogP_VSA10', 'SlogP_VSA11', 'SlogP_VSA12', 'SlogP_VSA2', 'SlogP_VSA3', 'SlogP_VSA4', 'SlogP_VSA5', 'SlogP_VSA6', 'SlogP_VSA7', 'SlogP_VSA8', 'SlogP_VSA9', 'TPSA', 'EState_VSA1', 'EState_VSA10', 'EState_VSA11', 'EState_VSA2', 'EState_VSA3', 'EState_VSA4', 'EState_VSA5', 'EState_VSA6', 'EState_VSA7', 'EState_VSA8', 'EState_VSA9', 'VSA_EState1', 'VSA_EState10', 'VSA_EState2', 'VSA_EState3', 'VSA_EState4', 'VSA_EState5', 'VSA_EState6', 'VSA_EState7', 'VSA_EState8', 'VSA_EState9', 'FractionCSP3', 'HeavyAtomCount', 'NHOHCount', 'NOCount', 'NumAliphaticCarbocycles', 'NumAliphaticHeterocycles', 'NumAliphaticRings', 'NumAromaticCarbocycles', 'NumAromaticHeterocycles', 'NumAromaticRings', 'NumHAcceptors', 'NumHDonors', 'NumHeteroatoms', 'NumRotatableBonds', 'NumSaturatedCarbocycles', 'NumSaturatedHeterocycles', 'NumSaturatedRings', 'RingCount', 'MolLogP', 'MolMR', 'fr_Al_COO', 'fr_Al_OH', 'fr_Al_OH_noTert', 'fr_ArN', 'fr_Ar_COO', 'fr_Ar_N', 'fr_Ar_NH', 'fr_Ar_OH', 'fr_COO', 'fr_COO2', 'fr_C_O', 'fr_C_O_noCOO', 'fr_C_S', 'fr_HOCCN', 'fr_Imine', 'fr_NH0', 'fr_NH1', 'fr_NH2', 'fr_N_O', 'fr_Ndealkylation1', 'fr_Ndealkylation2', 'fr_Nhpyrrole', 'fr_SH', 'fr_aldehyde', 'fr_alkyl_carbamate', 'fr_alkyl_halide', 'fr_allylic_oxid', 'fr_amide', 'fr_amidine', 'fr_aniline', 'fr_aryl_methyl', 'fr_azide', 'fr_azo', 'fr_barbitur', 'fr_benzene', 'fr_benzodiazepine', 'fr_bicyclic', 'fr_diazo', 'fr_dihydropyridine', 'fr_epoxide', 'fr_ester', 'fr_ether', 'fr_furan', 'fr_guanido', 'fr_halogen', 'fr_hdrzine', 'fr_hdrzone', 'fr_imidazole', 'fr_imide', 'fr_isocyan', 'fr_isothiocyan', 'fr_ketone', 'fr_ketone_Topliss', 'fr_lactam', 'fr_lactone', 'fr_methoxy', 'fr_morpholine', 'fr_nitrile', 'fr_nitro', 'fr_nitro_arom', 'fr_nitro_arom_nonortho', 'fr_nitroso', 'fr_oxazole', 'fr_oxime', 'fr_para_hydroxylation', 'fr_phenol', 'fr_phenol_noOrthoHbond', 'fr_phos_acid', 'fr_phos_ester', 'fr_piperdine', 'fr_piperzine', 'fr_priamide', 'fr_prisulfonamd', 'fr_pyridine', 'fr_quatN', 'fr_sulfide', 'fr_sulfonamd', 'fr_sulfone', 'fr_term_acetylene', 'fr_tetrazole', 'fr_thiazole', 'fr_thiocyan', 'fr_thiophene', 'fr_unbrch_alkane', 'fr_urea'])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create dictionary of rdkit calculations, to call the functions using their title\n",
    "metric_dict = {}\n",
    "for item in metric_list:\n",
    "    metric_dict[item[0]] = item[1]\n",
    "metric_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7c166c9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# after deciding which metrics we wish to use, we'll list them here\n",
    "metrics_to_add = ['MolWt','ExactMolWt','qed','MolLogP','LabuteASA','TPSA',\n",
    "                  'MaxPartialCharge','MinPartialCharge','MaxAbsPartialCharge','MinAbsPartialCharge',\n",
    "                  'NumHAcceptors','NumHDonors','HeavyAtomCount','NumHeteroatoms','NumRotatableBonds',\n",
    "                  'NHOHCount','NOCount','FractionCSP3','RingCount','NumAliphaticRings',\n",
    "                  'NumAromaticRings','NumAliphaticHeterocycles','NumAromaticHeterocycles','NumSaturatedHeterocycles',\n",
    "                  'NumSaturatedRings','MolMR','BalabanJ','BertzCT','HallKierAlpha','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3',\n",
    "                  'PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11',\n",
    "                  'PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5',\n",
    "                  'SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3',\n",
    "                  'SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10',\n",
    "                  'SlogP_VSA11','SlogP_VSA12']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7eac2aaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# now we can actually add the descriptor calculations to the data\n",
    "df = data\n",
    "\n",
    "for index,row in df.iterrows():\n",
    "    drugname = df.loc[index,'Name']\n",
    "    drugSMILES = df.loc[index,'smile']\n",
    "    drugmol = Chem.MolFromSmiles(drugSMILES)\n",
    "    \n",
    "    for metric in metrics_to_add:\n",
    "        function = metric_dict[metric]\n",
    "        \n",
    "        result = function(drugmol)\n",
    "        \n",
    "        df.loc[index,metric] = result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bb91d5d",
   "metadata": {},
   "source": [
    "* some of the metrics we've added provide amount of the drug's surface area (SA) having a given property within a certain range\n",
    "  * the full possible range of values for a property are divided into 10-14 subranges\n",
    "  * the metric tells you the amount of surface area for which that property's value lies within that subrange\n",
    "  * thus, if you add together all 10-14 subranges of a \"VSA\" metric, you get the molecule's total surface area\n",
    "* I would like to test whether it would be more relevant to describe instead the percentage of SA fitting that property range\n",
    "* thus, here I will create 'percent SA' alternatives for each \"VSA\" metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f5da5fab",
   "metadata": {},
   "outputs": [],
   "source": [
    "# list all VSA type of metrics\n",
    "VSAs = ['PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7',\n",
    "        'PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14',\n",
    "        'SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8',\n",
    "        'SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5',\n",
    "        'SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12']\n",
    "\n",
    "# list just one VSA metric, which can be summed for total surface area\n",
    "SMR_VSA = ['SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10']\n",
    "\n",
    "for index,row in df.iterrows():\n",
    "    drugname = df.loc[index,'Name']\n",
    "    drugSMILES = df.loc[index,'smile']\n",
    "    drugmol = Chem.MolFromSmiles(drugSMILES)\n",
    "    \n",
    "    # get the total SA for molecule\n",
    "    totalVSA = 0\n",
    "    for VSA_i in SMR_VSA: \n",
    "        totalVSA += df.loc[index,VSA_i]\n",
    "    df.loc[index,'VSA_total'] = totalVSA\n",
    "    \n",
    "    # express all VSA metrics in Percentage of total SA\n",
    "    for each_VSA in VSAs:\n",
    "        # lookup absolute value of each VSA metric\n",
    "        VSA_x = df.loc[index,each_VSA]\n",
    "        \n",
    "        # derive new name for VSA percentage column\n",
    "        if each_VSA[-2].isdigit():\n",
    "            num = f\"{each_VSA[-2]}{each_VSA[-1]}\"\n",
    "        else:\n",
    "            num = f\"0{each_VSA[-1]}\"\n",
    "        titleindex = each_VSA.index('_')\n",
    "        title = each_VSA[0:titleindex]\n",
    "        new_column_name = 'fracVSA_'+title+num\n",
    "        \n",
    "        # store value of relative percent VSA for each VSA metric\n",
    "        df.loc[index,new_column_name] = (VSA_x/totalVSA)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "047b09f9",
   "metadata": {},
   "source": [
    "* clean up and export"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9d9779fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# list of all current columns\n",
    "all_columns = ['Name','smile','BA_pct','MolWt','ExactMolWt','qed','MolLogP','LabuteASA','TPSA','MaxPartialCharge','MinPartialCharge','MaxAbsPartialCharge','MinAbsPartialCharge','NumHAcceptors','NumHDonors','HeavyAtomCount','NumHeteroatoms','NumRotatableBonds','NHOHCount','NOCount','FractionCSP3','RingCount','NumAliphaticRings','NumAromaticRings','NumAliphaticHeterocycles','NumAromaticHeterocycles','NumSaturatedHeterocycles','NumSaturatedRings','MolMR','BalabanJ','BertzCT','HallKierAlpha','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12','fracVSA_PEOE01','fracVSA_PEOE02','fracVSA_PEOE03','fracVSA_PEOE04','fracVSA_PEOE05','fracVSA_PEOE06','fracVSA_PEOE07','fracVSA_PEOE08','fracVSA_PEOE09','fracVSA_PEOE10','fracVSA_PEOE11','fracVSA_PEOE12','fracVSA_PEOE13','fracVSA_PEOE14','fracVSA_SMR01','fracVSA_SMR02','fracVSA_SMR03','fracVSA_SMR04','fracVSA_SMR05','fracVSA_SMR06','fracVSA_SMR07','fracVSA_SMR08','fracVSA_SMR09','fracVSA_SMR10','fracVSA_SlogP01','fracVSA_SlogP02','fracVSA_SlogP03','fracVSA_SlogP04','fracVSA_SlogP05','fracVSA_SlogP06','fracVSA_SlogP07','fracVSA_SlogP08','fracVSA_SlogP09','fracVSA_SlogP10','fracVSA_SlogP11','fracVSA_SlogP12','VSA_total','label1','label2','label3a','label3b']\n",
    "\n",
    "# re-order df columns\n",
    "new_col_order = ['Name','smile','BA_pct','label1','label2','label3a','label3b','MolWt','ExactMolWt','qed','MolLogP','MolMR','VSA_total','LabuteASA','TPSA','MaxPartialCharge','MinPartialCharge','MaxAbsPartialCharge','MinAbsPartialCharge','NumHAcceptors','NumHDonors','HeavyAtomCount','NumHeteroatoms','NumRotatableBonds','NHOHCount','NOCount','FractionCSP3','RingCount','NumAliphaticRings','NumAromaticRings','NumAliphaticHeterocycles','NumAromaticHeterocycles','NumSaturatedHeterocycles','NumSaturatedRings','BalabanJ','BertzCT','HallKierAlpha','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12','fracVSA_PEOE01','fracVSA_PEOE02','fracVSA_PEOE03','fracVSA_PEOE04','fracVSA_PEOE05','fracVSA_PEOE06','fracVSA_PEOE07','fracVSA_PEOE08','fracVSA_PEOE09','fracVSA_PEOE10','fracVSA_PEOE11','fracVSA_PEOE12','fracVSA_PEOE13','fracVSA_PEOE14','fracVSA_SMR01','fracVSA_SMR02','fracVSA_SMR03','fracVSA_SMR04','fracVSA_SMR05','fracVSA_SMR06','fracVSA_SMR07','fracVSA_SMR08','fracVSA_SMR09','fracVSA_SMR10','fracVSA_SlogP01','fracVSA_SlogP02','fracVSA_SlogP03','fracVSA_SlogP04','fracVSA_SlogP05','fracVSA_SlogP06','fracVSA_SlogP07','fracVSA_SlogP08','fracVSA_SlogP09','fracVSA_SlogP10','fracVSA_SlogP11','fracVSA_SlogP12']\n",
    "\n",
    "df_out = df[['Name','smile','BA_pct','label1','label2','label3a','label3b','MolWt','ExactMolWt','qed','MolLogP','MolMR','VSA_total','LabuteASA','TPSA','MaxPartialCharge','MinPartialCharge','MaxAbsPartialCharge','MinAbsPartialCharge','NumHAcceptors','NumHDonors','HeavyAtomCount','NumHeteroatoms','NumRotatableBonds','NHOHCount','NOCount','FractionCSP3','RingCount','NumAliphaticRings','NumAromaticRings','NumAliphaticHeterocycles','NumAromaticHeterocycles','NumSaturatedHeterocycles','NumSaturatedRings','BalabanJ','BertzCT','HallKierAlpha','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12','PEOE_VSA1','PEOE_VSA2','PEOE_VSA3','PEOE_VSA4','PEOE_VSA5','PEOE_VSA6','PEOE_VSA7','PEOE_VSA8','PEOE_VSA9','PEOE_VSA10','PEOE_VSA11','PEOE_VSA12','PEOE_VSA13','PEOE_VSA14','SMR_VSA1','SMR_VSA2','SMR_VSA3','SMR_VSA4','SMR_VSA5','SMR_VSA6','SMR_VSA7','SMR_VSA8','SMR_VSA9','SMR_VSA10','SlogP_VSA1','SlogP_VSA2','SlogP_VSA3','SlogP_VSA4','SlogP_VSA5','SlogP_VSA6','SlogP_VSA7','SlogP_VSA8','SlogP_VSA9','SlogP_VSA10','SlogP_VSA11','SlogP_VSA12','fracVSA_PEOE01','fracVSA_PEOE02','fracVSA_PEOE03','fracVSA_PEOE04','fracVSA_PEOE05','fracVSA_PEOE06','fracVSA_PEOE07','fracVSA_PEOE08','fracVSA_PEOE09','fracVSA_PEOE10','fracVSA_PEOE11','fracVSA_PEOE12','fracVSA_PEOE13','fracVSA_PEOE14','fracVSA_SMR01','fracVSA_SMR02','fracVSA_SMR03','fracVSA_SMR04','fracVSA_SMR05','fracVSA_SMR06','fracVSA_SMR07','fracVSA_SMR08','fracVSA_SMR09','fracVSA_SMR10','fracVSA_SlogP01','fracVSA_SlogP02','fracVSA_SlogP03','fracVSA_SlogP04','fracVSA_SlogP05','fracVSA_SlogP06','fracVSA_SlogP07','fracVSA_SlogP08','fracVSA_SlogP09','fracVSA_SlogP10','fracVSA_SlogP11','fracVSA_SlogP12']]\n",
    "\n",
    "# export\n",
    "df_out.to_csv('bioavailability_data_edit02.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57dfefb7",
   "metadata": {},
   "source": [
    "* verify the saved data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4388fe25",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>smile</th>\n",
       "      <th>BA_pct</th>\n",
       "      <th>label1</th>\n",
       "      <th>label2</th>\n",
       "      <th>label3a</th>\n",
       "      <th>label3b</th>\n",
       "      <th>MolWt</th>\n",
       "      <th>ExactMolWt</th>\n",
       "      <th>qed</th>\n",
       "      <th>...</th>\n",
       "      <th>fracVSA_SlogP03</th>\n",
       "      <th>fracVSA_SlogP04</th>\n",
       "      <th>fracVSA_SlogP05</th>\n",
       "      <th>fracVSA_SlogP06</th>\n",
       "      <th>fracVSA_SlogP07</th>\n",
       "      <th>fracVSA_SlogP08</th>\n",
       "      <th>fracVSA_SlogP09</th>\n",
       "      <th>fracVSA_SlogP10</th>\n",
       "      <th>fracVSA_SlogP11</th>\n",
       "      <th>fracVSA_SlogP12</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sulfadiazine</td>\n",
       "      <td>Nc1ccc(S(=O)(=O)Nc2ncccn2)cc1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>250.283</td>\n",
       "      <td>250.052447</td>\n",
       "      <td>0.787140</td>\n",
       "      <td>...</td>\n",
       "      <td>0.102152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.485327</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.118585</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>clofarabine</td>\n",
       "      <td>Nc1nc(Cl)nc2c1ncn2C1OC(CO)C(O)C1F</td>\n",
       "      <td>50.0</td>\n",
       "      <td>moderate</td>\n",
       "      <td>low</td>\n",
       "      <td>moderate</td>\n",
       "      <td>moderate</td>\n",
       "      <td>303.681</td>\n",
       "      <td>303.053445</td>\n",
       "      <td>0.648650</td>\n",
       "      <td>...</td>\n",
       "      <td>0.040835</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.053688</td>\n",
       "      <td>0.054545</td>\n",
       "      <td>0.045548</td>\n",
       "      <td>0.096239</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.088002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.100007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sulfamethoxazole</td>\n",
       "      <td>Cc1cc(NS(=O)(=O)c2ccc(N)cc2)no1</td>\n",
       "      <td>99.0</td>\n",
       "      <td>high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>253.283</td>\n",
       "      <td>253.052112</td>\n",
       "      <td>0.804737</td>\n",
       "      <td>...</td>\n",
       "      <td>0.102286</td>\n",
       "      <td>0.070655</td>\n",
       "      <td>0.058782</td>\n",
       "      <td>0.405645</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.117409</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tolazoline</td>\n",
       "      <td>c1ccc(CC2=NCCN2)cc1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>160.220</td>\n",
       "      <td>160.100048</td>\n",
       "      <td>0.691051</td>\n",
       "      <td>...</td>\n",
       "      <td>0.089738</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.077756</td>\n",
       "      <td>0.493697</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>cotinine</td>\n",
       "      <td>CN1C(=O)CCC1c1cccnc1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>very high</td>\n",
       "      <td>176.219</td>\n",
       "      <td>176.094963</td>\n",
       "      <td>0.647201</td>\n",
       "      <td>...</td>\n",
       "      <td>0.062586</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.319123</td>\n",
       "      <td>0.320161</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 145 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Name                              smile  BA_pct    label1  \\\n",
       "0      sulfadiazine      Nc1ccc(S(=O)(=O)Nc2ncccn2)cc1    90.0      high   \n",
       "1       clofarabine  Nc1nc(Cl)nc2c1ncn2C1OC(CO)C(O)C1F    50.0  moderate   \n",
       "2  sulfamethoxazole    Cc1cc(NS(=O)(=O)c2ccc(N)cc2)no1    99.0      high   \n",
       "3        tolazoline                c1ccc(CC2=NCCN2)cc1    90.0      high   \n",
       "4          cotinine               CN1C(=O)CCC1c1cccnc1    97.0      high   \n",
       "\n",
       "      label2    label3a    label3b    MolWt  ExactMolWt       qed  ...  \\\n",
       "0  very high  very high  very high  250.283  250.052447  0.787140  ...   \n",
       "1        low   moderate   moderate  303.681  303.053445  0.648650  ...   \n",
       "2  very high  very high  very high  253.283  253.052112  0.804737  ...   \n",
       "3  very high  very high  very high  160.220  160.100048  0.691051  ...   \n",
       "4  very high  very high  very high  176.219  176.094963  0.647201  ...   \n",
       "\n",
       "   fracVSA_SlogP03  fracVSA_SlogP04  fracVSA_SlogP05  fracVSA_SlogP06  \\\n",
       "0         0.102152         0.000000         0.000000         0.485327   \n",
       "1         0.040835         0.000000         0.053688         0.054545   \n",
       "2         0.102286         0.070655         0.058782         0.405645   \n",
       "3         0.089738         0.000000         0.077756         0.493697   \n",
       "4         0.062586         0.000000         0.319123         0.320161   \n",
       "\n",
       "   fracVSA_SlogP07  fracVSA_SlogP08  fracVSA_SlogP09  fracVSA_SlogP10  \\\n",
       "0         0.000000         0.000000              0.0         0.118585   \n",
       "1         0.045548         0.096239              0.0         0.088002   \n",
       "2         0.000000         0.000000              0.0         0.117409   \n",
       "3         0.000000         0.000000              0.0         0.000000   \n",
       "4         0.000000         0.000000              0.0         0.000000   \n",
       "\n",
       "   fracVSA_SlogP11  fracVSA_SlogP12  \n",
       "0              0.0         0.000000  \n",
       "1              0.0         0.100007  \n",
       "2              0.0         0.000000  \n",
       "3              0.0         0.000000  \n",
       "4              0.0         0.000000  \n",
       "\n",
       "[5 rows x 145 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reload saved data to verify\n",
    "import pandas as pd\n",
    "df = pd.read_csv('bioavailability_data_edit02.csv')\n",
    "df = df.drop(columns='Unnamed: 0')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60afcbde",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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