fingerprint_active_inactive.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\supak\\anaconda3\\envs\\my-rdkit-env\\lib\\site-packages\\umap\\distances.py:1063: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
      "  @numba.jit()\n",
      "c:\\Users\\supak\\anaconda3\\envs\\my-rdkit-env\\lib\\site-packages\\umap\\distances.py:1071: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
      "  @numba.jit()\n",
      "c:\\Users\\supak\\anaconda3\\envs\\my-rdkit-env\\lib\\site-packages\\umap\\distances.py:1086: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
      "  @numba.jit()\n",
      "c:\\Users\\supak\\anaconda3\\envs\\my-rdkit-env\\lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n",
      "c:\\Users\\supak\\anaconda3\\envs\\my-rdkit-env\\lib\\site-packages\\umap\\umap_.py:660: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
      "  @numba.jit()\n",
      "c:\\Users\\supak\\anaconda3\\envs\\my-rdkit-env\\lib\\site-packages\\umap\\plot.py:203: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n",
      "  @numba.jit()\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import rdkit\n",
    "import xlsxwriter\n",
    "from rdkit import Chem\n",
    "from rdkit.Chem import PandasTools\n",
    "from rdkit.Chem import Draw\n",
    "from rdkit.Chem.Draw import IPythonConsole\n",
    "from rdkit.Chem import Descriptors\n",
    "from rdkit.Chem import AllChem\n",
    "from rdkit import DataStructs\n",
    "from mordred import Calculator, descriptors\n",
    "from rdkit.Chem import rdFingerprintGenerator\n",
    "import matplotlib.pyplot as plt\n",
    "import umap.umap_ as umap\n",
    "import umap.plot\n",
    "from sklearn.cluster import SpectralClustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "           cid                                             smiles bioactivity  \\\n",
       "0    127024762  C[C@@H](CO)Nc1nc2ccccc2nc1N1CCN(Cc2cc(Cl)ccc2C...      Active   \n",
       "1    127024157  C[C@@H]1C[C@H]1Nc1nc2cnncc2nc1N1CCC([C@@H](F)c...      Active   \n",
       "2    155525744  C[C@H](CO)Nc1nc2ccccc2nc1N1CCN(Cc2cc(Cl)ccc2Cl...      Active   \n",
       "3     90038419   c1ccc2nc(N3CCN(Cc4coc5ccccc45)CC3)c(NC3CC3)nc2c1      Active   \n",
       "4     90038865  CC(=O)c1ccc(OC2CCN(c3nc4cnccc4nc3NC3CC3)CC2)cc...      Active   \n",
       "..         ...                                                ...         ...   \n",
       "401  127024707  O=C(O)C(F)(F)F.O=C(c1nccc2nc(NC3CC3)c(N3CCC([C...      Active   \n",
       "402  127024451  O=C(O)C(F)(F)F.Oc1ccc(OC2CCN(c3nc4ccncc4nc3NC3...      Active   \n",
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       "405   90038375  O=S(=O)(c1ccccc1)N1CCN(c2nc3ccccc3nc2Nc2cccnc2...      Active   \n",
       "\n",
       "     type  value (nM)     pIC50  \n",
       "0    IC50      1570.0  5.804100  \n",
       "1    IC50       145.0  6.838632  \n",
       "2    IC50      1570.0  5.804100  \n",
       "3    IC50      3960.0  5.402305  \n",
       "4    IC50      1740.0  5.759451  \n",
       "..    ...         ...       ...  \n",
       "401  IC50         6.0  8.221849  \n",
       "402  IC50        54.0  7.267606  \n",
       "403  IC50      9440.0  5.025028  \n",
       "404  IC50      5660.0  5.247184  \n",
       "405  IC50      4630.0  5.334419  \n",
       "\n",
       "[406 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"pIC50.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['mol_image'] = [Chem.MolFromSmiles(i) for i in df['smiles']]\n",
    "\n",
    "PandasTools.SaveXlsxFromFrame(df, 'mol_image.xlsx', molCol='mol_image')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 605.125x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 20))\n",
    "\n",
    "sns.displot(df, bins=20, x='pIC50', hue='bioactivity', kde=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def canonical_smiles(smiles):\n",
    "    mol_smiles = [Chem.MolFromSmiles(smi) for smi in smiles]\n",
    "    smiles = [Chem.MolToSmiles(mol) for mol in mol_smiles]\n",
    "\n",
    "    return smiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "406"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CANNO_SMILES = canonical_smiles(df.smiles)\n",
    "len(CANNO_SMILES)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Unnamed: 0</th>\n",
       "      <th>cid</th>\n",
       "      <th>smiles</th>\n",
       "      <th>bioactivity</th>\n",
       "      <th>type</th>\n",
       "      <th>value (nM)</th>\n",
       "      <th>pIC50</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>118159240</td>\n",
       "      <td>CC(=O)N1CCc2nc(N3CCC(C(=O)c4cc(Cl)ccc4F)CC3)c(...</td>\n",
       "      <td>Active</td>\n",
       "      <td>IC50</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>10.860121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>118180377</td>\n",
       "      <td>CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CN(C(=...</td>\n",
       "      <td>Active</td>\n",
       "      <td>IC50</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>10.860121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>118180376</td>\n",
       "      <td>CC(=O)N1CCc2nc(N3CCC(Oc4ccc(F)cc4F)[C@H](F)C3)...</td>\n",
       "      <td>Active</td>\n",
       "      <td>IC50</td>\n",
       "      <td>0.0378</td>\n",
       "      <td>10.422508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>118180374</td>\n",
       "      <td>CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CCN(CN...</td>\n",
       "      <td>Active</td>\n",
       "      <td>IC50</td>\n",
       "      <td>0.0626</td>\n",
       "      <td>10.203426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>127024467</td>\n",
       "      <td>Cc1nccc2nc(NC3CC3)c(N3CCC(Cc4ccc(F)cc4F)CC3)nc...</td>\n",
       "      <td>Active</td>\n",
       "      <td>IC50</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>8.698970</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>401</th>\n",
       "      <td>401</td>\n",
       "      <td>118159281</td>\n",
       "      <td>CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CCN(C(...</td>\n",
       "      <td>Inactive</td>\n",
       "      <td>IC50</td>\n",
       "      <td>340200.0000</td>\n",
       "      <td>3.468266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>402</td>\n",
       "      <td>118159155</td>\n",
       "      <td>COc1cccc(S(=O)(=O)C2CCN(c3nc4c(nc3NC(C)C)CCN(C...</td>\n",
       "      <td>Inactive</td>\n",
       "      <td>IC50</td>\n",
       "      <td>341500.0000</td>\n",
       "      <td>3.466609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>403</td>\n",
       "      <td>118159118</td>\n",
       "      <td>CC(=O)N1CCc2nc(N3CCN(Cc4ccc(C#N)cc4F)CC3)c(NC(...</td>\n",
       "      <td>Inactive</td>\n",
       "      <td>IC50</td>\n",
       "      <td>362900.0000</td>\n",
       "      <td>3.440213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>404</td>\n",
       "      <td>118159228</td>\n",
       "      <td>CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CCN(C(...</td>\n",
       "      <td>Inactive</td>\n",
       "      <td>IC50</td>\n",
       "      <td>391000.0000</td>\n",
       "      <td>3.407823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>405</td>\n",
       "      <td>118159128</td>\n",
       "      <td>CC(=O)OC1CC(Nc2nc3c(nc2N2CCC(Oc4ccc(F)cc4F)CC2...</td>\n",
       "      <td>Inactive</td>\n",
       "      <td>IC50</td>\n",
       "      <td>603900.0000</td>\n",
       "      <td>3.219035</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>406 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0        cid                                             smiles  \\\n",
       "0             0  118159240  CC(=O)N1CCc2nc(N3CCC(C(=O)c4cc(Cl)ccc4F)CC3)c(...   \n",
       "1             1  118180377  CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CN(C(=...   \n",
       "2             2  118180376  CC(=O)N1CCc2nc(N3CCC(Oc4ccc(F)cc4F)[C@H](F)C3)...   \n",
       "3             3  118180374  CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CCN(CN...   \n",
       "4             4  127024467  Cc1nccc2nc(NC3CC3)c(N3CCC(Cc4ccc(F)cc4F)CC3)nc...   \n",
       "..          ...        ...                                                ...   \n",
       "401         401  118159281  CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CCN(C(...   \n",
       "402         402  118159155  COc1cccc(S(=O)(=O)C2CCN(c3nc4c(nc3NC(C)C)CCN(C...   \n",
       "403         403  118159118  CC(=O)N1CCc2nc(N3CCN(Cc4ccc(C#N)cc4F)CC3)c(NC(...   \n",
       "404         404  118159228  CC(C)Nc1nc2c(nc1N1CCC(Oc3ccc(F)cc3F)CC1)CCN(C(...   \n",
       "405         405  118159128  CC(=O)OC1CC(Nc2nc3c(nc2N2CCC(Oc4ccc(F)cc4F)CC2...   \n",
       "\n",
       "    bioactivity  type   value (nM)      pIC50  \n",
       "0        Active  IC50       0.0138  10.860121  \n",
       "1        Active  IC50       0.0138  10.860121  \n",
       "2        Active  IC50       0.0378  10.422508  \n",
       "3        Active  IC50       0.0626  10.203426  \n",
       "4        Active  IC50       2.0000   8.698970  \n",
       "..          ...   ...          ...        ...  \n",
       "401    Inactive  IC50  340200.0000   3.468266  \n",
       "402    Inactive  IC50  341500.0000   3.466609  \n",
       "403    Inactive  IC50  362900.0000   3.440213  \n",
       "404    Inactive  IC50  391000.0000   3.407823  \n",
       "405    Inactive  IC50  603900.0000   3.219035  \n",
       "\n",
       "[406 rows x 7 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['smiles'] = CANNO_SMILES\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Morgan Fingerprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(<rdkit.Chem.rdchem.Mol at 0x1f67d66a3b0>, 'Active', 10.860120913598765),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67d6689e0>, 'Active', 10.860120913598765),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67d6683c0>, 'Active', 10.422508200162774),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67d668350>, 'Active', 10.20342566678957),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67d668510>, 'Active', 8.698970004336019)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compounds_morgan = []\n",
    "\n",
    "for _, smiles, bioactivity, pIC50 in df[['smiles', 'bioactivity', 'pIC50']].itertuples():\n",
    "    compounds_morgan.append((Chem.MolFromSmiles(smiles), bioactivity, pIC50))\n",
    "compounds_morgan[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Structure</th>\n",
       "      <th>bioactivity</th>\n",
       "      <th>pIC50</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67D6...</td>\n",
       "      <td>Active</td>\n",
       "      <td>10.860121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67D6...</td>\n",
       "      <td>Active</td>\n",
       "      <td>10.860121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67D6...</td>\n",
       "      <td>Active</td>\n",
       "      <td>10.422508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67D6...</td>\n",
       "      <td>Active</td>\n",
       "      <td>10.203426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67D6...</td>\n",
       "      <td>Active</td>\n",
       "      <td>8.698970</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Structure bioactivity      pIC50\n",
       "0  <rdkit.Chem.rdchem.Mol object at 0x000001F67D6...      Active  10.860121\n",
       "1  <rdkit.Chem.rdchem.Mol object at 0x000001F67D6...      Active  10.860121\n",
       "2  <rdkit.Chem.rdchem.Mol object at 0x000001F67D6...      Active  10.422508\n",
       "3  <rdkit.Chem.rdchem.Mol object at 0x000001F67D6...      Active  10.203426\n",
       "4  <rdkit.Chem.rdchem.Mol object at 0x000001F67D6...      Active   8.698970"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compounds_morgan_structure = pd.DataFrame(compounds_morgan, columns=[\"Structure\", \"bioactivity\", \"pIC50\"])\n",
    "compounds_morgan_structure.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of compounds converted: 406\n",
      "Fingerprint length per compound: 2048\n"
     ]
    }
   ],
   "source": [
    "def generate_mfpts(data):\n",
    "    Mfpts = [AllChem.GetMorganFingerprintAsBitVect(mol, 2, nBits=2048) for mol in data]\n",
    "    return Mfpts\n",
    "\n",
    "mfpts = generate_mfpts(compounds_morgan_structure.Structure[:])\n",
    "print(\"Number of compounds converted:\", len(mfpts))\n",
    "print(\"Fingerprint length per compound:\", len(mfpts[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>bioactivity</th>\n",
       "      <th>Bit_0</th>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2049 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  bioactivity  Bit_0  Bit_1  Bit_2  Bit_3  Bit_4  Bit_5  Bit_6  Bit_7  Bit_8  \\\n",
       "0      Active      0      1      0      0      0      0      0      0      0   \n",
       "1      Active      0      1      0      0      0      0      0      0      0   \n",
       "2      Active      0      1      0      0      0      0      0      0      0   \n",
       "3      Active      0      1      0      0      0      0      0      0      0   \n",
       "4      Active      0      0      0      0      0      0      0      0      0   \n",
       "\n",
       "   ...  Bit_2038  Bit_2039  Bit_2040  Bit_2041  Bit_2042  Bit_2043  Bit_2044  \\\n",
       "0  ...         0         0         0         0         0         0         0   \n",
       "1  ...         0         0         0         0         0         0         0   \n",
       "2  ...         0         0         0         0         0         0         0   \n",
       "3  ...         0         0         0         0         0         0         0   \n",
       "4  ...         0         0         0         0         0         0         0   \n",
       "\n",
       "   Bit_2045  Bit_2046  Bit_2047  \n",
       "0         0         0         0  \n",
       "1         0         0         0  \n",
       "2         0         0         0  \n",
       "3         0         0         0  \n",
       "4         0         0         0  \n",
       "\n",
       "[5 rows x 2049 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp_name_morgan = [f'Bit_{i}' for i in range(2048)]\n",
    "fp_bits_morgan = [list(l) for l in mfpts]\n",
    "\n",
    "morganfp_df = pd.DataFrame(fp_bits_morgan, index=df[\"bioactivity\"], columns=fp_name_morgan)\n",
    "morganfp_df.reset_index(inplace=True)  # Reset index to bring \"cid\" back as a column\n",
    "morganfp_df.rename(columns={\"index\": \"bioactivity\"})# Rename the index column to \"cid\"\n",
    "morganfp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>401</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>406 rows × 2048 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Bit_0  Bit_1  Bit_2  Bit_3  Bit_4  Bit_5  Bit_6  Bit_7  Bit_8  Bit_9  \\\n",
       "0        0      1      0      0      0      0      0      0      0      0   \n",
       "1        0      1      0      0      0      0      0      0      0      0   \n",
       "2        0      1      0      0      0      0      0      0      0      0   \n",
       "3        0      1      0      0      0      0      0      0      0      0   \n",
       "4        0      0      0      0      0      0      0      0      0      1   \n",
       "..     ...    ...    ...    ...    ...    ...    ...    ...    ...    ...   \n",
       "401      0      1      0      0      0      0      0      0      0      0   \n",
       "402      0      1      0      0      0      0      0      0      0      0   \n",
       "403      0      1      0      0      0      0      0      0      0      0   \n",
       "404      0      1      0      0      0      0      0      0      0      0   \n",
       "405      0      0      0      0      0      0      0      0      0      0   \n",
       "\n",
       "     ...  Bit_2038  Bit_2039  Bit_2040  Bit_2041  Bit_2042  Bit_2043  \\\n",
       "0    ...         0         0         0         0         0         0   \n",
       "1    ...         0         0         0         0         0         0   \n",
       "2    ...         0         0         0         0         0         0   \n",
       "3    ...         0         0         0         0         0         0   \n",
       "4    ...         0         0         0         0         0         0   \n",
       "..   ...       ...       ...       ...       ...       ...       ...   \n",
       "401  ...         0         0         0         0         0         0   \n",
       "402  ...         0         0         0         0         0         0   \n",
       "403  ...         0         0         0         0         0         0   \n",
       "404  ...         1         0         0         0         0         0   \n",
       "405  ...         0         0         0         0         0         0   \n",
       "\n",
       "     Bit_2044  Bit_2045  Bit_2046  Bit_2047  \n",
       "0           0         0         0         0  \n",
       "1           0         0         0         0  \n",
       "2           0         0         0         0  \n",
       "3           0         0         0         0  \n",
       "4           0         0         0         0  \n",
       "..        ...       ...       ...       ...  \n",
       "401         0         0         0         0  \n",
       "402         0         0         0         0  \n",
       "403         0         0         0         0  \n",
       "404         0         0         0         0  \n",
       "405         0         0         0         0  \n",
       "\n",
       "[406 rows x 2048 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "morganfp_df_umap = morganfp_df.iloc[:, 1:]\n",
    "morganfp_df_umap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "RDK5 Fingerprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(<rdkit.Chem.rdchem.Mol at 0x1f67f823680>, 'Active'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67f8236f0>, 'Active'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67f823f40>, 'Active'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67f823760>, 'Active'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x1f67f823c30>, 'Active')]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compounds_rdk5 = []\n",
    "\n",
    "for _, smiles, bioactivity in df[['smiles', 'bioactivity']].itertuples():\n",
    "    compounds_rdk5.append((Chem.MolFromSmiles(smiles), bioactivity))\n",
    "compounds_rdk5[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Structure</th>\n",
       "      <th>bioactivity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Active</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Active</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Active</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Active</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Active</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>401</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Inactive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Inactive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Inactive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Inactive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>&lt;rdkit.Chem.rdchem.Mol object at 0x000001F67F8...</td>\n",
       "      <td>Inactive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>406 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Structure bioactivity\n",
       "0    <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...      Active\n",
       "1    <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...      Active\n",
       "2    <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...      Active\n",
       "3    <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...      Active\n",
       "4    <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...      Active\n",
       "..                                                 ...         ...\n",
       "401  <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...    Inactive\n",
       "402  <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...    Inactive\n",
       "403  <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...    Inactive\n",
       "404  <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...    Inactive\n",
       "405  <rdkit.Chem.rdchem.Mol object at 0x000001F67F8...    Inactive\n",
       "\n",
       "[406 rows x 2 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compound_rdk5_structure = pd.DataFrame(compounds_rdk5, columns=[\"Structure\", \"bioactivity\"])\n",
    "compound_rdk5_structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of compounds converted: 406\n",
      "Fingerprint length per compound: 2048\n"
     ]
    }
   ],
   "source": [
    "def generate_rdk5(data):\n",
    "    rdk5_gen = rdFingerprintGenerator.GetRDKitFPGenerator(maxPath=5)\n",
    "    rdk5_fingerprint = [rdk5_gen.GetFingerprint(mol) for mol in data]\n",
    "    return rdk5_fingerprint\n",
    "\n",
    "rdk5fp = generate_rdk5(compound_rdk5_structure.Structure[:])\n",
    "print(\"Number of compounds converted:\", len(rdk5fp))\n",
    "print(\"Fingerprint length per compound:\", len(rdk5fp[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bioactivity</th>\n",
       "      <th>Bit_0</th>\n",
       "      <th>Bit_1</th>\n",
       "      <th>Bit_2</th>\n",
       "      <th>Bit_3</th>\n",
       "      <th>Bit_4</th>\n",
       "      <th>Bit_5</th>\n",
       "      <th>Bit_6</th>\n",
       "      <th>Bit_7</th>\n",
       "      <th>Bit_8</th>\n",
       "      <th>...</th>\n",
       "      <th>Bit_2038</th>\n",
       "      <th>Bit_2039</th>\n",
       "      <th>Bit_2040</th>\n",
       "      <th>Bit_2041</th>\n",
       "      <th>Bit_2042</th>\n",
       "      <th>Bit_2043</th>\n",
       "      <th>Bit_2044</th>\n",
       "      <th>Bit_2045</th>\n",
       "      <th>Bit_2046</th>\n",
       "      <th>Bit_2047</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2049 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  bioactivity  Bit_0  Bit_1  Bit_2  Bit_3  Bit_4  Bit_5  Bit_6  Bit_7  Bit_8  \\\n",
       "0      Active      1      0      0      0      0      1      0      0      0   \n",
       "1      Active      1      0      0      0      0      1      0      0      0   \n",
       "2      Active      1      0      0      0      0      1      0      0      0   \n",
       "3      Active      1      0      0      0      0      1      0      0      0   \n",
       "4      Active      1      0      0      0      0      1      0      0      0   \n",
       "\n",
       "   ...  Bit_2038  Bit_2039  Bit_2040  Bit_2041  Bit_2042  Bit_2043  Bit_2044  \\\n",
       "0  ...         1         0         0         0         0         0         1   \n",
       "1  ...         0         0         0         0         0         0         1   \n",
       "2  ...         0         0         0         0         0         0         1   \n",
       "3  ...         0         0         0         0         0         0         1   \n",
       "4  ...         1         0         0         1         0         0         1   \n",
       "\n",
       "   Bit_2045  Bit_2046  Bit_2047  \n",
       "0         0         0         1  \n",
       "1         0         0         1  \n",
       "2         0         0         1  \n",
       "3         0         0         1  \n",
       "4         0         0         1  \n",
       "\n",
       "[5 rows x 2049 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp_name_rdk5 = [f'Bit_{i}' for i in range(2048)]\n",
    "fp_bits_rdk5 = [list(l) for l in rdk5fp]\n",
    "\n",
    "rdk5_df = pd.DataFrame(fp_bits_rdk5, index=df[\"bioactivity\"], columns=fp_name_rdk5)\n",
    "rdk5_df.reset_index(inplace=True)  # Reset index to bring \"cid\" back as a column\n",
    "rdk5_df.rename(columns={\"index\": \"bioactivity\"})# Rename the index column to \"cid\"\n",
    "rdk5_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>405</th>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>406 rows × 2048 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Bit_0  Bit_1  Bit_2  Bit_3  Bit_4  Bit_5  Bit_6  Bit_7  Bit_8  Bit_9  \\\n",
       "0        1      0      0      0      0      1      0      0      0      0   \n",
       "1        1      0      0      0      0      1      0      0      0      0   \n",
       "2        1      0      0      0      0      1      0      0      0      0   \n",
       "3        1      0      0      0      0      1      0      0      0      0   \n",
       "4        1      0      0      0      0      1      0      0      0      0   \n",
       "..     ...    ...    ...    ...    ...    ...    ...    ...    ...    ...   \n",
       "401      1      0      0      0      0      1      0      0      0      0   \n",
       "402      1      0      0      0      0      1      0      0      0      0   \n",
       "403      1      0      0      0      0      1      0      0      0      0   \n",
       "404      1      0      0      0      0      1      0      0      0      0   \n",
       "405      1      0      0      0      0      1      0      0      0      0   \n",
       "\n",
       "     ...  Bit_2038  Bit_2039  Bit_2040  Bit_2041  Bit_2042  Bit_2043  \\\n",
       "0    ...         1         0         0         0         0         0   \n",
       "1    ...         0         0         0         0         0         0   \n",
       "2    ...         0         0         0         0         0         0   \n",
       "3    ...         0         0         0         0         0         0   \n",
       "4    ...         1         0         0         1         0         0   \n",
       "..   ...       ...       ...       ...       ...       ...       ...   \n",
       "401  ...         0         0         0         0         0         0   \n",
       "402  ...         0         0         0         0         0         1   \n",
       "403  ...         1         0         0         0         0         0   \n",
       "404  ...         0         0         0         0         0         0   \n",
       "405  ...         0         0         0         0         0         0   \n",
       "\n",
       "     Bit_2044  Bit_2045  Bit_2046  Bit_2047  \n",
       "0           1         0         0         1  \n",
       "1           1         0         0         1  \n",
       "2           1         0         0         1  \n",
       "3           1         0         0         1  \n",
       "4           1         0         0         1  \n",
       "..        ...       ...       ...       ...  \n",
       "401         1         0         0         1  \n",
       "402         1         0         0         1  \n",
       "403         1         0         0         1  \n",
       "404         1         0         0         1  \n",
       "405         1         0         0         1  \n",
       "\n",
       "[406 rows x 2048 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdk5_df_umap = rdk5_df.iloc[:, 1:]\n",
    "rdk5_df_umap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " UMAP Morgan Fingerprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "umapper = umap.UMAP(n_neighbors=20, \n",
    "                    n_components=5,\n",
    "                    metric='euclidean', \n",
    "                    random_state=42\n",
    "                    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_umap_morgan = umapper.fit_transform(morganfp_df_umap)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
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       "      <th>404</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>7.023235</td>\n",
       "      <td>14.800626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>7.452923</td>\n",
       "      <td>14.297009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>406 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bioactivity         x          y\n",
       "0        Active  8.133041  12.629872\n",
       "1        Active  7.150947  14.930597\n",
       "2        Active  7.213410  14.633593\n",
       "3        Active  7.406426  14.389816\n",
       "4        Active  9.695139  -0.625216\n",
       "..          ...       ...        ...\n",
       "401    Inactive  7.054058  14.642127\n",
       "402    Inactive  7.850706  13.245184\n",
       "403    Inactive  8.401472  13.499196\n",
       "404    Inactive  7.023235  14.800626\n",
       "405    Inactive  7.452923  14.297009\n",
       "\n",
       "[406 rows x 3 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_umap_morgan_x = pd.DataFrame(data_umap_morgan[:, 0], columns = ['x'])\n",
    "data_umap_morgan_y = pd.DataFrame(data_umap_morgan[:, 1], columns = ['y'])\n",
    "bioactivity = pd.DataFrame(morganfp_df[\"bioactivity\"].values, columns = ['bioactivity'])\n",
    "plot_umap_morgan = pd.concat([bioactivity, data_umap_morgan_x, data_umap_morgan_y], axis = 1)\n",
    "plot_umap_morgan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (7, 5), dpi=120)\n",
    "sns.scatterplot(x='x', y='y', hue='bioactivity', data=plot_umap_morgan, palette='bright')\n",
    "plt.xlabel(\"UMAP Component 1\")\n",
    "plt.ylabel(\"UMAP Component 2\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.title('UMAP with Morgan Fingerprint', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "UMAP with RDK5 Fingerprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "umapper = umap.UMAP(n_neighbors=20, \n",
    "                    n_components=5,\n",
    "                    metric='euclidean', \n",
    "                    random_state=42,\n",
    "                    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_umap_rdk5 = umapper.fit_transform(rdk5_df_umap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>bioactivity</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Active</td>\n",
       "      <td>7.634721</td>\n",
       "      <td>-0.820363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Active</td>\n",
       "      <td>13.564285</td>\n",
       "      <td>-0.629351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Active</td>\n",
       "      <td>12.480776</td>\n",
       "      <td>1.313320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Active</td>\n",
       "      <td>13.654971</td>\n",
       "      <td>-0.412328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Active</td>\n",
       "      <td>1.360735</td>\n",
       "      <td>8.581531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>401</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>12.437316</td>\n",
       "      <td>1.527752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>12.209198</td>\n",
       "      <td>1.108529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>9.627057</td>\n",
       "      <td>-0.479728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>13.525257</td>\n",
       "      <td>-0.621144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>Inactive</td>\n",
       "      <td>12.764761</td>\n",
       "      <td>1.379709</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>406 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bioactivity          x         y\n",
       "0        Active   7.634721 -0.820363\n",
       "1        Active  13.564285 -0.629351\n",
       "2        Active  12.480776  1.313320\n",
       "3        Active  13.654971 -0.412328\n",
       "4        Active   1.360735  8.581531\n",
       "..          ...        ...       ...\n",
       "401    Inactive  12.437316  1.527752\n",
       "402    Inactive  12.209198  1.108529\n",
       "403    Inactive   9.627057 -0.479728\n",
       "404    Inactive  13.525257 -0.621144\n",
       "405    Inactive  12.764761  1.379709\n",
       "\n",
       "[406 rows x 3 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_umap_rdk5_x = pd.DataFrame(data_umap_rdk5[:, 0], columns = ['x'])\n",
    "data_umap_rdk5_y = pd.DataFrame(data_umap_rdk5[:, 1], columns = ['y'])\n",
    "bioactivity = pd.DataFrame(rdk5_df[\"bioactivity\"].values, columns = ['bioactivity'])\n",
    "plot_umap_rdk5 = pd.concat([bioactivity, data_umap_rdk5_x, data_umap_rdk5_y], axis = 1)\n",
    "plot_umap_rdk5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (7, 5), dpi=120)\n",
    "sns.scatterplot(x='x', y='y', hue='bioactivity', data=plot_umap_rdk5, palette='bright')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.title('UMAP with RDK5 fingerprint', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clustering by Butina of Morgan FP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdkit.ML.Cluster import Butina"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "def tanimoto_distance_matrix(fp_list):\n",
    "    \n",
    "    dissimilarity_matrix = []\n",
    "    \n",
    "    for i in range(1, len(fp_list)):\n",
    "        \n",
    "        similarities = DataStructs.BulkTanimotoSimilarity(fp_list[i], fp_list[:i])\n",
    "        dissimilarity_matrix.extend([1 - x for x in similarities])\n",
    "    return dissimilarity_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tanimoto similarity: 0.42, distance: 0.58\n"
     ]
    }
   ],
   "source": [
    "sim = DataStructs.TanimotoSimilarity(mfpts[0], mfpts[1])\n",
    "print(f\"Tanimoto similarity: {sim:.2f}, distance: {1-sim:.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.5842696629213483,\n",
       " 0.4375,\n",
       " 0.44047619047619047,\n",
       " 0.5909090909090908,\n",
       " 0.45238095238095233,\n",
       " 0.4642857142857143,\n",
       " 0.7373737373737373,\n",
       " 0.7156862745098039,\n",
       " 0.7128712871287128,\n",
       " 0.7352941176470589,\n",
       " 0.6363636363636364,\n",
       " 0.42500000000000004,\n",
       " 0.5119047619047619,\n",
       " 0.4691358024691358,\n",
       " 0.5795454545454546,\n",
       " 0.7422680412371134,\n",
       " 0.5116279069767442,\n",
       " 0.6344086021505376,\n",
       " 0.6,\n",
       " 0.5730337078651686,\n",
       " 0.4358974358974359,\n",
       " 0.7570093457943925,\n",
       " 0.6886792452830188,\n",
       " 0.7339449541284404,\n",
       " 0.6826923076923077,\n",
       " 0.43181818181818177,\n",
       " 0.5851063829787234,\n",
       " 0.59375,\n",
       " 0.6105263157894737,\n",
       " 0.5161290322580645,\n",
       " 0.63,\n",
       " 0.5979381443298969,\n",
       " 0.6568627450980392,\n",
       " 0.3291139240506329,\n",
       " 0.345679012345679,\n",
       " 0.6574074074074074,\n",
       " 0.6363636363636364,\n",
       " 0.5681818181818181,\n",
       " 0.6111111111111112,\n",
       " 0.6222222222222222,\n",
       " 0.5632183908045977,\n",
       " 0.26086956521739135,\n",
       " 0.5977011494252873,\n",
       " 0.4534883720930233,\n",
       " 0.5,\n",
       " 0.6483516483516483,\n",
       " 0.5,\n",
       " 0.5934065934065934,\n",
       " 0.5568181818181819,\n",
       " 0.6526315789473685,\n",
       " 0.16417910447761197,\n",
       " 0.5294117647058824,\n",
       " 0.6534653465346535,\n",
       " 0.35365853658536583,\n",
       " 0.381578947368421,\n",
       " 0.731958762886598,\n",
       " 0.6701030927835052,\n",
       " 0.7070707070707071,\n",
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       " ...]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tanimoto_distance_matrix(mfpts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elements in the triangular matrix (82215) == tanimoto_distance_matrix(mfpts) (82215)\n"
     ]
    }
   ],
   "source": [
    "n = len(mfpts)\n",
    "\n",
    "elem_triangular_matr = (n * (n - 1)) / 2\n",
    "\n",
    "print(\n",
    "    f\"Elements in the triangular matrix ({elem_triangular_matr:.0f}) ==\",\n",
    "    f\"tanimoto_distance_matrix(mfpts) ({len(tanimoto_distance_matrix(mfpts))})\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cluster_mfpts(fingerprints, cutoff=0.3):\n",
    "\n",
    "    distance_matrix = tanimoto_distance_matrix(mfpts)\n",
    "    clusters = Butina.ClusterData(distance_matrix, len(mfpts), cutoff, isDistData=True)\n",
    "    clusters = sorted(clusters, key=len, reverse=True)\n",
    "    return clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for cutoff in np.arange(0.0, 1.0, 0.1):\n",
    "    clusters = cluster_mfpts(mfpts, cutoff=cutoff)\n",
    "    fig, ax = plt.subplots(figsize=(15, 4))\n",
    "    ax.set_title(f\"Threshold: {cutoff:3.1f}\")\n",
    "    ax.set_xlabel(\"Cluster index\")\n",
    "    ax.set_ylabel(\"Number of molecules\")\n",
    "    ax.bar(range(1, len(clusters) + 1), [len(c) for c in clusters], lw=5)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 8.133041 , 12.629872 ,  3.5366704,  5.674887 , 11.429842 ],\n",
       "       [ 7.1509466, 14.930597 ,  3.3869026,  6.0852966, 11.4692   ],\n",
       "       [ 7.21341  , 14.633593 ,  3.059802 ,  5.8123765, 10.937122 ],\n",
       "       ...,\n",
       "       [ 8.401472 , 13.499196 ,  2.838627 ,  6.0699906, 10.212026 ],\n",
       "       [ 7.023235 , 14.800626 ,  3.0269916,  5.804219 , 11.221627 ],\n",
       "       [ 7.4529233, 14.297009 ,  2.9622042,  5.9587603, 10.571577 ]],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_umap_morgan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot Each Clusters by UMAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 840x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start with UMAP\n",
    "umapper = umap.UMAP(n_neighbors=20, \n",
    "                    n_components=5,\n",
    "                    metric='euclidean',\n",
    "                    random_state=5\n",
    "                    )\n",
    "\n",
    "data_umap_morgan = umapper.fit_transform(morganfp_df_umap)\n",
    "\n",
    "# Apply Butina functions\n",
    "cutoff = 0.7\n",
    "clusters = cluster_mfpts(data_umap_morgan, cutoff=cutoff)\n",
    "\n",
    "\n",
    "# Create a scatter plot using Seaborn\n",
    "for cluster_index, cluster in enumerate(clusters, start=1):\n",
    "    cluster_molecule_indices = cluster \n",
    "    \n",
    "    cluster_coords = data_umap_morgan[cluster_molecule_indices, :]\n",
    "    \n",
    "    x_coords = cluster_coords[:, 0]\n",
    "    y_coords = cluster_coords[:, 1]\n",
    "    \n",
    "    cluster_labels = np.full(len(cluster_molecule_indices), f\"Cluster {cluster_index}\")\n",
    "    \n",
    "    \n",
    "    data_umap_morgan_x = pd.DataFrame(x_coords, columns = ['x'])\n",
    "    data_umap_morgan_y = pd.DataFrame(y_coords, columns = ['y'])\n",
    "    bioactivity = pd.DataFrame(morganfp_df[\"bioactivity\"].values, columns = ['bioactivity'])\n",
    "    plot_umap_morgan_butina = pd.concat([bioactivity, data_umap_morgan_x, data_umap_morgan_y], axis = 1)\n",
    "    plot_umap_morgan_butina\n",
    "    \n",
    "    plt.figure(figsize=(7, 5), dpi=120)\n",
    "    sns.scatterplot(x=\"x\", y=\"y\", hue='bioactivity' , data=plot_umap_morgan_butina, palette='bright')\n",
    "    plt.xlabel(\"UMAP Component 1\")\n",
    "    plt.ylabel(\"UMAP Component 2\")\n",
    "    plt.title(f\"Cluster {cluster_index}_Morgan FP\")\n",
    "    \n",
    "    cluster_size = len(cluster_molecule_indices)\n",
    "    mean_x = np.mean(data_umap_morgan[cluster_molecule_indices, 0])\n",
    "    mean_y = np.mean(data_umap_morgan[cluster_molecule_indices, 1])\n",
    "    plt.annotate(f\"Count: {cluster_size}\", (mean_x, mean_y), xytext=(0, 10),textcoords=\"offset points\", ha='center', fontsize=8)\n",
    "\n",
    "    plt.legend()\n",
    "    plt.grid()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Draw.MolsToGridImage(\n",
    "    [compounds_morgan_structure[\"Structure\"][clusters[i][0]] for i in range(6)],\n",
    "    molsPerRow=6,\n",
    "    legends=[\n",
    "        f\"{compounds_morgan_structure['bioactivity'][clusters[i][0]]}, pIC50 = {compounds_morgan_structure['pIC50'][clusters[i][0]]:.4f}\"\n",
    "        for i in range(6)]\n",
    ")"
   ]
  }
 ],
 "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": "3.10.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}