Notebooks/createSMILES.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c58c3fa0",
   "metadata": {},
   "source": [
    "Notebook to create SMILES of search space molecules\n",
    "\n",
    "SD | FergLab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "acf45029",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rdkit\n",
    "from rdkit import Chem\n",
    "from rdkit.Chem import AllChem\n",
    "from rdkit.Chem.Draw import IPythonConsole\n",
    "from rdkit.Chem.Draw import MolDrawing, DrawingOptions\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"../Codes/\")\n",
    "import utils_activeLearning_Oliver as ut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bc7762e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "DrawingOptions.bondLineWidth=1.8\n",
    "DrawingOptions.atomLabelFontSize=14\n",
    "DrawingOptions.includeAtomNumbers=False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3edfa201",
   "metadata": {},
   "source": [
    "Functions to generate molecules using RDKit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5e06c4cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to mutate an atom\n",
    "def mutate(rdmol, idx, element):\n",
    "    \n",
    "    #print(idx)\n",
    "\n",
    "    editMol = Chem.EditableMol(rdmol)\n",
    "    \n",
    "    #print(Chem.MolToSmiles(editMol.GetMol()))\n",
    "\n",
    "    editMol.ReplaceAtom(idx, Chem.Atom(element))\n",
    "    \n",
    "    #print(Chem.MolToSmiles(editMol.GetMol()))\n",
    "    \n",
    "    for nbrs in reversed(rdmol.GetAtomWithIdx(idx).GetNeighbors()):\n",
    "        \n",
    "        #print(nbrs.GetSymbol())\n",
    "        if nbrs.GetSymbol() == 'H' or nbrs.GetSymbol() == 'F' or nbrs.GetSymbol() == 'Cl' or nbrs.GetSymbol() == 'Br':\n",
    "            \n",
    "            #print(Chem.MolToSmiles(rdmol))\n",
    "            editMol.RemoveAtom(nbrs.GetIdx())\n",
    "            \n",
    "    #print(Chem.MolToSmiles(editMol.GetMol()))\n",
    "            \n",
    "    #editMol.ReplaceAtom(idx, Chem.Atom(element))\n",
    "    \n",
    "    mutant = editMol.GetMol()\n",
    "    Chem.SanitizeMol(mutant)\n",
    "    mutant = Chem.AddHs(mutant, addCoords=True)\n",
    "    \n",
    "    return Chem.MolToSmiles( Chem.RemoveHs(mutant) )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb806e9c",
   "metadata": {},
   "source": [
    "Generate molecules;\n",
    "\n",
    "Note: molecule_names list variable below is not used (only serves to keep track of molecule names)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bd1e0122",
   "metadata": {},
   "outputs": [],
   "source": [
    "molecules = []\n",
    "\n",
    "molecules_names = []\n",
    "\n",
    "for i in range(4,15):\n",
    "\n",
    "    #molecules.append( Chem.MolFromSmiles('C'*i) )\n",
    "    \n",
    "    mol = Chem.MolFromSmiles('C'*i)\n",
    "    \n",
    "    # append linear hydrocarbons\n",
    "    molecules.append(Chem.MolToSmiles( mol) )\n",
    "    \n",
    "        \n",
    "    label_i_c_count = Chem.MolToSmiles(mol).count('C')\n",
    "    molecules_names.append('c' + str(label_i_c_count))\n",
    "    \n",
    "    # add explicit hydrogens to SMILES\n",
    "    mol = Chem.AddHs(mol)\n",
    "    \n",
    "    # find index of carbons\n",
    "    c_index = []\n",
    "    \n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        if atom.GetAtomicNum() == 6:\n",
    "            c_index.append(atom.GetIdx())\n",
    "        \n",
    "    # debug indices   \n",
    "    #c_index\n",
    "        \n",
    "        \n",
    "    for at_num in [9, 17, 35]:\n",
    "        \n",
    "        c_index_copy = c_index.copy()\n",
    "        \n",
    "        for j in range(i):\n",
    "        \n",
    "            edit1 = Chem.RWMol(mol)\n",
    "        \n",
    "            # replace selected atoms with \n",
    "            for atom in edit1.GetAtoms():\n",
    "            \n",
    "                if atom.GetAtomicNum() == 6:\n",
    "            \n",
    "                #for j in range(i):\n",
    "                \n",
    "                    if atom.GetIdx() in c_index_copy:\n",
    "                    \n",
    "                        #print(c_index_copy, atom.GetIdx())\n",
    "                    \n",
    "                        for nbr in atom.GetNeighbors():\n",
    "                        \n",
    "                            if nbr.GetAtomicNum() == 1:\n",
    "                            \n",
    "                                nbr.SetAtomicNum(at_num)\n",
    "                            \n",
    "            \n",
    "                            \n",
    "            #print(c_index_copy)\n",
    "            #print(j)\n",
    "            c_index_copy.pop(0)\n",
    "        \n",
    "            Chem.SanitizeMol(edit1)\n",
    "            edit1_mol = Chem.RemoveHs(edit1)\n",
    "            molecules.append(Chem.MolToSmiles( edit1_mol) )\n",
    "            \n",
    "            label_i_c_count = Chem.MolToSmiles(mol).count('c')\n",
    "            if at_num == 9:\n",
    "                label_i_halogen_count =  'f' + str(Chem.MolToSmiles(mol).count('F'))\n",
    "            elif at_num == 17:\n",
    "                label_i_halogen_count =  'cl' + str(Chem.MolToSmiles(mol).count('Cl') )\n",
    "            elif at_num == 35:\n",
    "                label_i_halogen_count =  'br' + str(Chem.MolToSmiles(mol).count('Br') )\n",
    "                \n",
    "            molecules_names.append('c' + str(label_i_c_count) + '-' + label_i_halogen_count)\n",
    "            \n",
    "\n",
    "primary_molecules = []         \n",
    "for i in range(len(molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(molecules[i])\n",
    "    \n",
    "    # find head and tail C index; remove duplicates later\n",
    "\n",
    "    c_index = []\n",
    "    \n",
    "    for atom in mol.GetAtoms():\n",
    "        if atom.GetAtomicNum() == 6:\n",
    "            c_index.append(atom.GetIdx())\n",
    "      \n",
    "    #print(c_index)\n",
    "            \n",
    "    # mutate head and tail C with NH2\n",
    "    \n",
    "    new_mol1  = mutate(Chem.AddHs(mol), c_index[0], 'N')\n",
    "    new_mol2  = mutate(Chem.AddHs(mol), c_index[-1], 'N')\n",
    "    \n",
    "    primary_molecules.append(new_mol1)\n",
    "    primary_molecules.append(new_mol2)\n",
    "        \n",
    "    # debug indices   \n",
    "    #c_index\n",
    "    \n",
    "secondary_molecules = []\n",
    "for i in range(len(primary_molecules)):\n",
    "    \n",
    "    mol = Chem.AddHs( Chem.MolFromSmiles(primary_molecules[i]) )\n",
    "    \n",
    "    # find head and tail C index; remove duplicates later\n",
    "\n",
    "    h_index = []\n",
    "    \n",
    "    for atom in mol.GetAtoms():\n",
    "        \n",
    "        if atom.GetSymbol() == 'N':\n",
    "                        \n",
    "            for nbr in atom.GetNeighbors():\n",
    "                                        \n",
    "                if nbr.GetAtomicNum() == 1:\n",
    "                                        \n",
    "                    h_index.append(nbr.GetIdx())\n",
    "      \n",
    "    #print(c_index)\n",
    "    \n",
    "    #print(h_index)\n",
    "            \n",
    "    # mutate head and tail C with NH2\n",
    "    \n",
    "    new_mol1  = mutate(mol, h_index[0], 'C')\n",
    "    \n",
    "    secondary_molecules.append(new_mol1)\n",
    "        \n",
    "    # debug indices   \n",
    "    #c_index\n",
    "    \n",
    "tertiary_molecules = []\n",
    "for i in range(len(secondary_molecules)):\n",
    "    \n",
    "    mol = Chem.AddHs( Chem.MolFromSmiles(secondary_molecules[i]) )\n",
    "    \n",
    "    # find head and tail C index; remove duplicates later\n",
    "\n",
    "    h_index = []\n",
    "    \n",
    "    for atom in mol.GetAtoms():\n",
    "        \n",
    "        if atom.GetSymbol() == 'N':\n",
    "                        \n",
    "            for nbr in atom.GetNeighbors():\n",
    "                                        \n",
    "                if nbr.GetAtomicNum() == 1:\n",
    "                                        \n",
    "                    h_index.append(nbr.GetIdx())\n",
    "      \n",
    "    #print(c_index)\n",
    "    \n",
    "    #print(h_index)\n",
    "            \n",
    "    # mutate head and tail C with NH2\n",
    "    \n",
    "    new_mol1  = mutate(mol, h_index[0], 'C')\n",
    "    \n",
    "    tertiary_molecules.append(new_mol1)\n",
    "        \n",
    "    # debug indices   \n",
    "    #c_index\n",
    "    \n",
    "    \n",
    "primary_phos_molecules = []         \n",
    "for i in range(len(molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(molecules[i])\n",
    "    \n",
    "    # find head and tail C index; remove duplicates later\n",
    "\n",
    "    c_index = []\n",
    "    \n",
    "    for atom in mol.GetAtoms():\n",
    "        if atom.GetAtomicNum() == 6:\n",
    "            c_index.append(atom.GetIdx())\n",
    "      \n",
    "    #print(c_index)\n",
    "            \n",
    "    # mutate head and tail C with NH2\n",
    "    \n",
    "    new_mol1  = mutate(Chem.AddHs(mol), c_index[0], 'P')\n",
    "    new_mol2  = mutate(Chem.AddHs(mol), c_index[-1], 'P')\n",
    "    \n",
    "    primary_phos_molecules.append(new_mol1)\n",
    "    primary_phos_molecules.append(new_mol2)\n",
    "        \n",
    "    # debug indices   \n",
    "    #c_index\n",
    "    \n",
    "secondary_phos_molecules = [] \n",
    "for i in range(len(primary_phos_molecules)):\n",
    "    \n",
    "    mol = Chem.AddHs( Chem.MolFromSmiles(primary_phos_molecules[i]) )\n",
    "    \n",
    "    # find head and tail C index; remove duplicates later\n",
    "\n",
    "    h_index = []\n",
    "    \n",
    "    for atom in mol.GetAtoms():\n",
    "        \n",
    "        if atom.GetSymbol() == 'P':\n",
    "                        \n",
    "            for nbr in atom.GetNeighbors():\n",
    "                                        \n",
    "                if nbr.GetAtomicNum() == 1:\n",
    "                                        \n",
    "                    h_index.append(nbr.GetIdx())\n",
    "    \n",
    "    new_mol1  = mutate(mol, h_index[0], 'C')\n",
    "    \n",
    "    secondary_phos_molecules.append(new_mol1)\n",
    "    \n",
    "\n",
    "tertiary_phos_molecules = []\n",
    "for i in range(len(secondary_phos_molecules)):\n",
    "    \n",
    "    mol = Chem.AddHs( Chem.MolFromSmiles(secondary_phos_molecules[i]) )\n",
    "    \n",
    "    # find head and tail C index; remove duplicates later\n",
    "\n",
    "    h_index = []\n",
    "    \n",
    "    for atom in mol.GetAtoms():\n",
    "        \n",
    "        if atom.GetSymbol() == 'P':\n",
    "                        \n",
    "            for nbr in atom.GetNeighbors():\n",
    "                                        \n",
    "                if nbr.GetAtomicNum() == 1:\n",
    "                                        \n",
    "                    h_index.append(nbr.GetIdx())\n",
    "    \n",
    "    new_mol1  = mutate(mol, h_index[0], 'C')\n",
    "    \n",
    "    tertiary_phos_molecules.append(new_mol1)\n",
    "    \n",
    "    \n",
    "    \n",
    "primary_charged_molecules = []         \n",
    "for i in range(len(primary_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(primary_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    idx1 = edit.AddAtom(Chem.Atom(1))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        \n",
    "        if atom.GetAtomicNum() == 7:\n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "    \n",
    "    primary_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "    \n",
    "secondary_charged_molecules = []         \n",
    "for i in range(len(primary_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(primary_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    idx1 = edit.AddAtom(Chem.Atom(6))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        \n",
    "        if atom.GetAtomicNum() == 7:\n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "    \n",
    "    secondary_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "tertiary_charged_molecules = []         \n",
    "for i in range(len(secondary_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(secondary_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    idx1 = edit.AddAtom(Chem.Atom(6))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        \n",
    "        if atom.GetAtomicNum() == 7:\n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "    \n",
    "    tertiary_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    " \n",
    "    \n",
    "primary_phos_charged_molecules = []         \n",
    "for i in range(len(primary_phos_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(primary_phos_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    idx1 = edit.AddAtom(Chem.Atom(1))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        \n",
    "        if atom.GetAtomicNum() == 15:\n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "    \n",
    "    primary_phos_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "    \n",
    "secondary_phos_charged_molecules = []         \n",
    "for i in range(len(primary_phos_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(primary_phos_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    idx1 = edit.AddAtom(Chem.Atom(6))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        \n",
    "        if atom.GetAtomicNum() == 15:\n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "    \n",
    "    secondary_phos_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "tertiary_phos_charged_molecules = []         \n",
    "for i in range(len(secondary_phos_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(secondary_phos_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(mol)\n",
    "    idx1 = edit.AddAtom(Chem.Atom(6))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "        \n",
    "        if atom.GetAtomicNum() == 15:\n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "    \n",
    "    tertiary_phos_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "    \n",
    "quaternary_charged_molecules = []         \n",
    "for i in range(len(tertiary_charged_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(tertiary_charged_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(Chem.AddHs(mol))\n",
    "    idx1 = edit.AddAtom(Chem.Atom(6))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "    \n",
    "        if atom.GetAtomicNum() == 7:\n",
    "        \n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "            for nbr in atom.GetNeighbors():\n",
    "            \n",
    "                if nbr.GetAtomicNum() == 1:\n",
    "                    idx3 = nbr.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE)\n",
    "    edit.RemoveAtom(idx3) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "\n",
    "    quaternary_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "    \n",
    "quaternary_phos_charged_molecules = []         \n",
    "for i in range(len(tertiary_phos_charged_molecules)):\n",
    "    \n",
    "    mol = Chem.MolFromSmiles(tertiary_phos_charged_molecules[i])\n",
    "\n",
    "    # prepare for editing\n",
    "    edit = Chem.RWMol(Chem.AddHs(mol))\n",
    "    idx1 = edit.AddAtom(Chem.Atom(6))\n",
    "    \n",
    "    for atom in edit.GetAtoms():\n",
    "    \n",
    "        if atom.GetAtomicNum() == 15:\n",
    "        \n",
    "            idx2 = atom.GetIdx()\n",
    "        \n",
    "            for nbr in atom.GetNeighbors():\n",
    "            \n",
    "                if nbr.GetAtomicNum() == 1:\n",
    "                    idx3 = nbr.GetIdx()\n",
    "        \n",
    "    bondIdx = edit.AddBond(idx1,idx2, Chem.BondType.SINGLE)\n",
    "    edit.RemoveAtom(idx3) \n",
    "    edit.GetAtomWithIdx(idx2).SetFormalCharge(1)\n",
    "    Chem.SanitizeMol(edit)\n",
    "    edit_mol = Chem.RemoveHs(edit)\n",
    "\n",
    "    quaternary_phos_charged_molecules.append(Chem.MolToSmiles(edit_mol))\n",
    "    \n",
    "    \n",
    "#molecules = list(set(molecules))\n",
    "#molecules_names = list(set(molecules_names))\n",
    "#\n",
    "#primary_molecules = list(set(primary_molecules))\n",
    "#secondary_molecules = list(set(secondary_molecules))\n",
    "#tertiary_molecules = list(set(tertiary_molecules))\n",
    "#\n",
    "#primary_phos_molecules = list(set(primary_phos_molecules))\n",
    "#secondary_phos_molecules = list(set(secondary_phos_molecules))\n",
    "#tertiary_phos_molecules = list(set(tertiary_phos_molecules))\n",
    "#\n",
    "#primary_charged_molecules = list(set(primary_charged_molecules))\n",
    "#secondary_charged_molecules = list(set(secondary_charged_molecules))\n",
    "#tertiary_charged_molecules = list(set(tertiary_charged_molecules))\n",
    "#\n",
    "#primary_phos_charged_molecules = list(set(primary_phos_charged_molecules))\n",
    "#secondary_phos_charged_molecules = list(set(secondary_phos_charged_molecules))\n",
    "#tertiary_phos_charged_molecules = list(set(tertiary_phos_charged_molecules))\n",
    "#\n",
    "#quaternary_charged_molecules = list(set(quaternary_charged_molecules))\n",
    "#quaternary_phos_charged_molecules = list(set(quaternary_phos_charged_molecules))\n",
    "#\n",
    "#\n",
    "#all_molecules = molecules + primary_molecules + secondary_molecules + tertiary_molecules\n",
    "#all_molecules = all_molecules + primary_phos_molecules + secondary_phos_molecules + tertiary_phos_molecules\n",
    "##all_molecules += primary_charged_molecules + secondary_charged_molecules + tertiary_charged_molecules\n",
    "##all_molecules += primary_phos_charged_molecules + secondary_phos_charged_molecules + tertiary_phos_charged_molecules\n",
    "#\n",
    "#all_molecules += quaternary_charged_molecules\n",
    "##all_molecules += quaternary_phos_charged_molecules\n",
    "#\n",
    "#\n",
    "#all_molecules_df = pd.DataFrame(all_molecules, columns =['smiles']) \n",
    "#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ada13d17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f746385e760>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot\n",
    "Chem.MolFromSmiles( quaternary_charged_molecules[0] )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2488a94",
   "metadata": {},
   "source": [
    "For naming molecules using SMILES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd59f3c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "probeNames = []\n",
    "for i in range(selected_probes_df.shape[0]):\n",
    "    \n",
    "    smiles = selected_probes_df.smiles.values[i]\n",
    "    \n",
    "    label_i_c_count = smiles.count('C')\n",
    "    \n",
    "    label_i_f_count = smiles.count('F')\n",
    "    \n",
    "    label_i_cl_count = smiles.count('Cl')\n",
    "    \n",
    "    label_i_br_count = smiles.count('Br')\n",
    "    \n",
    "    if label_i_cl_count != 0:\n",
    "        label_i_c_count -= label_i_cl_count\n",
    "        \n",
    "    fstring = '-f'\n",
    "    if label_i_cl_count > 0:\n",
    "        label_i_f_count = label_i_cl_count\n",
    "        fstring = '-cl'\n",
    "        \n",
    "    if label_i_br_count > 0:\n",
    "        label_i_f_count = label_i_br_count\n",
    "        fstring = '-br'\n",
    "        \n",
    "        \n",
    "     \n",
    "    countP = -1\n",
    "    if smiles.count('P') > 0:\n",
    "        \n",
    "        countP = smiles.count('P')\n",
    "        smiles = smiles.replace('P', 'N')\n",
    "        \n",
    "    \n",
    "    rdkProbe = Chem.MolFromSmiles(smiles, sanitize=True)\n",
    "    \n",
    "    label_i_head_group_h_count = -1\n",
    "    label_i_head_group_c_count = -1\n",
    "    \n",
    "    if fr_NH2(rdkProbe) == 1 and fr_quatN(rdkProbe) == 0 :\n",
    "        label_i_head_group_h_count = 2\n",
    "        label_i_head_group_c_count = 0\n",
    "        #print(probes[i], \"primary amine\")\n",
    "    elif fr_NH1(rdkProbe) == 1 and fr_quatN(rdkProbe) == 0:\n",
    "        label_i_head_group_h_count = 1\n",
    "        label_i_head_group_c_count = 1\n",
    "        #print(probes[i], \"secondary amine\")\n",
    "    elif fr_NH0(rdkProbe) == 1 and fr_quatN(rdkProbe) == 0:\n",
    "        label_i_head_group_h_count = 0\n",
    "        label_i_head_group_c_count = 2\n",
    "        #label_i_head_group = \"0\"\n",
    "        #print(probes[i], \"tertiary amine\")\n",
    "    elif fr_NH0(rdkProbe) == 1 and fr_quatN(rdkProbe) == 1:\n",
    "        label_i_head_group_h_count = 0\n",
    "        label_i_head_group_c_count = 3\n",
    "        #label_i_head_group = \"\"\n",
    "        #print(probes[i], \"quaternary amine\")\n",
    "    elif fr_NH2(rdkProbe) == 1 and fr_quatN(rdkProbe) == 1 :\n",
    "        label_i_head_group_h_count = 2\n",
    "        label_i_head_group_c_count = 1\n",
    "        #print(probes[i], \"secondary amine cation\") \n",
    "    elif fr_NH1(rdkProbe) == 1 and fr_quatN(rdkProbe) == 1:\n",
    "        label_i_head_group_h_count = 1\n",
    "        label_i_head_group_c_count = 2\n",
    "        #print(probes[i], \"tertiary amine cation\")\n",
    "    elif fr_NH0(rdkProbe) == 0 and fr_quatN(rdkProbe) == 1:\n",
    "        label_i_head_group_h_count = 3\n",
    "        label_i_head_group_c_count = 0\n",
    "\n",
    "    if label_i_head_group_c_count > 0:\n",
    "        label_i_c_count = label_i_c_count - label_i_head_group_c_count\n",
    "    \n",
    "    if countP == -1:\n",
    "    \n",
    "        if label_i_head_group_h_count == -1 and label_i_head_group_c_count == -1:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count)\n",
    "        elif label_i_head_group_h_count == 0:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count) + '-n' + '(ch3)' + str(label_i_head_group_c_count)\n",
    "        elif label_i_head_group_c_count == 0:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count) + '-nh' + str(label_i_head_group_h_count)\n",
    "        elif label_i_head_group_h_count > 0 and label_i_head_group_c_count > 0:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count) + '-nh' + str(label_i_head_group_h_count) + '(ch3)' + str(label_i_head_group_c_count)\n",
    "    else:\n",
    "        \n",
    "        if label_i_head_group_h_count == -1 and label_i_head_group_c_count == -1:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count)\n",
    "        elif label_i_head_group_h_count == 0:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count) + '-p' + '(ch3)' + str(label_i_head_group_c_count)\n",
    "        elif label_i_head_group_c_count == 0:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count) + '-ph' + str(label_i_head_group_h_count)\n",
    "        elif label_i_head_group_h_count > 0 and label_i_head_group_c_count > 0:\n",
    "            label_i = 'c' + str(label_i_c_count) + fstring + str(label_i_f_count) + '-ph' + str(label_i_head_group_h_count) + '(ch3)' + str(label_i_head_group_c_count)\n",
    "        \n",
    "    \n",
    "    probeName = label_i\n",
    "    \n",
    "    probeNames.append(probeName)\n",
    "    print(probeName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ab0bddd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41d2678d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bce489d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#all_molecules = quaternary_phos_charged_molecules\n",
    "#all_molecules_df = pd.DataFrame(all_molecules, columns =['smiles'])\n",
    "\n",
    "# DO NOT EXIST IN TRAINING SET (SO NO LATENT REPRESENTATION; THEREFORE EXCLUDING THESE COMBINATIONS)\n",
    "# primary_charged_molecules + secondary_charged_molecules + tertiary_charged_molecules\n",
    "# primary_phos_charged_molecules + secondary_phos_charged_molecules + tertiary_phos_charged_molecules\n",
    "# quaternary_phos_charged_molecules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "9d491e81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4356"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "8*506+308"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "2c2ecd4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "308\n",
      "506\n",
      "506\n",
      "506\n",
      "3850\n",
      "506\n",
      "506\n",
      "506\n",
      "506\n",
      "506\n",
      "506\n",
      "506\n",
      "506\n",
      "506\n",
      "3850\n"
     ]
    }
   ],
   "source": [
    "print(len(molecules))\n",
    "print(len(primary_molecules))\n",
    "print(len(secondary_molecules))\n",
    "print(len(tertiary_molecules))\n",
    "print(len(all_molecules))\n",
    "print(len(primary_phos_molecules))\n",
    "print(len(primary_charged_molecules))\n",
    "print(len(secondary_charged_molecules))\n",
    "print(len(tertiary_charged_molecules))\n",
    "print(len(primary_phos_charged_molecules))\n",
    "print(len(secondary_phos_charged_molecules))\n",
    "print(len(tertiary_phos_charged_molecules))\n",
    "print(len(quaternary_charged_molecules))\n",
    "print(len(quaternary_phos_charged_molecules))\n",
    "print(len(all_molecules))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a06d000e",
   "metadata": {},
   "source": [
    "Filter molecules based on alphabets used in trianing VAE --- requires utils codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "206d19eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['[epsilon]', '[C]', '[=C]', '[C@Hexpl]', '[N]', '[Ring1]', '[Branch1_1]', '[C@@Hexpl]', '[Branch1_3]', '[=O]', '[O]', '[Branch2_3]', '[Branch2_1]', '[=N]', '[c]', '[F]', '[Ring2]', '[Branch1_2]', '[o]', '[n]', '[S]', '[Branch2_2]', '[#N]', '[#C]', '[=S]', '[s]', '[-c]', '[Cl]', '[=c]', '[/C]', '[/c]', '[Br]', '[-n]', '[nHexpl]', '[=N+expl]', '[O-expl]', '[N+expl]', '[C@expl]', '[C@@expl]', '[/N]', '[\\\\S]', '[\\\\c]', '[.]', '[n+expl]', '[/O]', '[Expl-Ring1]', '[\\\\C]', '[P]', '[/S]', '[\\\\N]', '[\\\\O]', '[I]', '[Siexpl]', '[S@@expl]', '[S@expl]']\n",
      "(3850, 2)\n"
     ]
    }
   ],
   "source": [
    "# filter probes using alphabet list extracted from the training set molecules\n",
    "alphabet_list = pd.read_csv('codes/data/alphabet-list.csv')['alphabets'].tolist()\n",
    "print(alphabet_list)\n",
    "\n",
    "alpha_exists = ut.check_molecules_alphabets_exists(all_molecules_df)\n",
    "\n",
    "#print(\"\\n probes alphabet list\")\n",
    "#print(alpha_exists)\n",
    "\n",
    "all_molecules_df['smilesValid'] = np.array(alpha_exists)\n",
    "\n",
    "all_molecules_dfValid = all_molecules_df[ (all_molecules_df.smilesValid == True) ]\n",
    "\n",
    "print(all_molecules_dfValid.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "1767976c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4356, 2)\n",
      "(506, 2)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7f6f63abaca0>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_molecules_dfInvalid = all_molecules_df[ (all_molecules_df.smilesValid == False) ]\n",
    "print( all_molecules_df.shape  )\n",
    "print( all_molecules_dfInvalid.shape )\n",
    "Chem.MolFromSmiles( all_molecules_dfInvalid.smiles.values[20] )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fe4d19f",
   "metadata": {},
   "source": [
    "Save to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "791a3377",
   "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>smiles</th>\n",
       "      <th>smilesValid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CCCCCCCCCCCC(Br)(Br)Br</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)Br</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CCCCCCCC(Br)(Br)Br</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CCCCCCC(F)(F)C(F)(F)C(F)(F)F</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3845</th>\n",
       "      <td>CCCCCCCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)[...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3846</th>\n",
       "      <td>C[N+](C)(C)CCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3847</th>\n",
       "      <td>CCCCCCCC(F)(F)[N+](C)(C)C</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3848</th>\n",
       "      <td>C[N+](C)(C)CCCC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3849</th>\n",
       "      <td>C[N+](C)(C)CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(B...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3850 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 smiles  smilesValid\n",
       "0                                CCCCCCCCCCCC(Br)(Br)Br         True\n",
       "1      CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)Br         True\n",
       "2                                    CCCCCCCC(Br)(Br)Br         True\n",
       "3                          CCCCCCC(F)(F)C(F)(F)C(F)(F)F         True\n",
       "4     CCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...         True\n",
       "...                                                 ...          ...\n",
       "3845  CCCCCCCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)[...         True\n",
       "3846  C[N+](C)(C)CCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...         True\n",
       "3847                          CCCCCCCC(F)(F)[N+](C)(C)C         True\n",
       "3848  C[N+](C)(C)CCCC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)...         True\n",
       "3849  C[N+](C)(C)CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(B...         True\n",
       "\n",
       "[3850 rows x 2 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_molecules_dfValid.to_csv(\"../Data/VAE_data/SMILES_linearProbes_All.csv\", columns=['smiles'], index=False)\n",
    "all_molecules_dfValid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "0c7a4824",
   "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>smiles</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CCCCCCCCCCCC(Br)(Br)Br</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)Br</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CCCCCCCC(Br)(Br)Br</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CCCCCCC(F)(F)C(F)(F)C(F)(F)F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3845</th>\n",
       "      <td>CCCCCCCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)[...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3846</th>\n",
       "      <td>C[N+](C)(C)CCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3847</th>\n",
       "      <td>CCCCCCCC(F)(F)[N+](C)(C)C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3848</th>\n",
       "      <td>C[N+](C)(C)CCCC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3849</th>\n",
       "      <td>C[N+](C)(C)CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3850 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 smiles\n",
       "0                                CCCCCCCCCCCC(Br)(Br)Br\n",
       "1      CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(Br)Br\n",
       "2                                    CCCCCCCC(Br)(Br)Br\n",
       "3                          CCCCCCC(F)(F)C(F)(F)C(F)(F)F\n",
       "4     CCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...\n",
       "...                                                 ...\n",
       "3845  CCCCCCCCCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)[...\n",
       "3846  C[N+](C)(C)CCC(Cl)(Cl)C(Cl)(Cl)C(Cl)(Cl)C(Cl)(...\n",
       "3847                          CCCCCCCC(F)(F)[N+](C)(C)C\n",
       "3848  C[N+](C)(C)CCCC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)...\n",
       "3849  C[N+](C)(C)CC(Br)(Br)C(Br)(Br)C(Br)(Br)C(Br)(B...\n",
       "\n",
       "[3850 rows x 1 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_molecules_dfValid = pd.read_csv(\"../Data/VAE_data/SMILES_linearProbes_All.csv\")\n",
    "\n",
    "all_molecules_dfValid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 535,
   "id": "5fd6048c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x7fa6dbc96b80>"
      ]
     },
     "execution_count": 535,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Chem.MolFromSmiles( tertiary_molecules[2] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f77c889",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}