iwatobipen/lig3dlens_test.ipynb

## lig3dlens_test.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ce8c2a46-6bb7-46af-86fc-7046f93e1c20",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "from rdkit import Chem\n",
    "from rdkit.Chem.Draw import IPythonConsole\n",
    "from rdkit.Chem import PandasTools\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7d5de496-0a92-428c-813d-31d49fe63195",
   "metadata": {},
   "outputs": [],
   "source": [
    "PandasTools.RenderImagesInAllDataFrames(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "53a373dc-00a7-4f53-888b-1dc2c4392624",
   "metadata": {},
   "outputs": [],
   "source": [
    "active_df = PandasTools.LoadSDF('./cdk2/actives_align.sdf')\n",
    "decoy_df = PandasTools.LoadSDF('./cdk2/decoys_align.sdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "23ef372d-305e-42e2-8f87-f517d249f401",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/iwatobipen/miniforge3/envs/lig3dlens/lib/python3.10/site-packages/rdkit/Chem/PandasPatcher.py:132: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "  for col in df_subset.columns[df_subset.applymap(MolFormatter.is_mol).any()]\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CPD_ID</th>\n",
       "      <th>SC_RDKit_score</th>\n",
       "      <th>ESPSim</th>\n",
       "      <th>ShapeSim</th>\n",
       "      <th>ID</th>\n",
       "      <th>ROMol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHEMBL426972</td>\n",
       "      <td>0.4272</td>\n",
       "      <td>-0.0106</td>\n",
       "      <td>0.3889</td>\n",
       "      <td></td>\n",
       "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img 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\" alt=\"Mol\"/></div></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHEMBL519715</td>\n",
       "      <td>0.5138</td>\n",
       "      <td>-0.0258</td>\n",
       "      <td>0.4642</td>\n",
       "      <td></td>\n",
       "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAADICAIAAAAiOjnJAAAABmJLR0QA/wD/AP+gvaeTAAAaoUlEQVR4nO3deVhV1d4H8O/eZwKZRFBBRGVSBHEENIfQlOtYGo6hmEN2u3rT6jXN4Wqm18LCIev14sUiUzPTLqmlr2MWOCHiCCoXFVSUQGU8DOewf+8fGwHNSuwcFmezPk9/eDbnnP07z/NtrXXW2XstgYjAcaYmsi6AUyYeLM4seLA4s+DB4syCB4szCx4szix4sDiz4MHizMLCgnX79u2//OUvRUVFrAvh/oBgQTPvRqNRp9NJkjRs2LC4uDiVSsW6Iu43WUyLZTAY1Gp1t27dAOzevXvGjBmsK+J+j+rdd99lXcMfu3PnTv/+/Y1Go7u7++HDh9VqdWJiok6n69OnD+vSuMezjBbrwIEDSUlJs2bNsrKyAtCiRQuVSrVgwYLY2FjWpXG/gSzE4sWLAVhbW1tZWQmCsGLFCgAajWbPnj2sS+MewzJaLADvvvvu9OnTS0pKKioqiKhVq1bz5s0zGAwjR448fvw46+q4X2Gd7FowGo0jRoyQy46IiJAkadKkSQCaNm165coV1tVxD7GkYBGRXq8PCAgAYGVlVVhYWF5ePnDgQABeXl7Z2dmsq+OqWViwiOjOnTuiKALo1atXWVlZQUFB165dAQQFBeXm5rKujqtkecEioueee07uEMPDwyVJunz5spubmyiKnTp1Yl0aV8liBu81DR06FIBard6yZcvkyZOfeeaZJk2aADh79uzu3btZV8cBljKP9QhfX19BECRJ0mg0X375pSAI58+f7927N4Bly5aR5fxIpWAWGawhQ4Y0adJEkqTnnntu69at8hTX7du3XVxcTpw4ERcXx7pAzqKmG2o6ffq0KIpWVlYZGRnl5eXe3t4AwsPDAbRt27a8vJx1gQ2dZfxW+Guurq6pqalnz54tKCh48cUXmzdvvn379rt377Zo0eLKlSuurq5BQUGsa2zYWCf76V29elWn06lUqvPnz0uS1KNHDzxotJo1a5afn8+6wAbNgoNFRK+//jqAYcOGEdGPP/4IwM7OLjg4GMDixYtZV9egWXawcnJy7O3tARw8eJCIBg8eDGDs2LGCINjY2GRlZbEusOGy7GAR0dKlSwEEBwdLknTu3DmVSqXVakNDQwG89tprrKtruCw+WHq9vmXLlgC++eYbInr55ZcBDB06VKPRqFSqixcvsi6wgbL4YBFRdHQ0AE9Pz7Kysps3bzZq1EgQhLCwMAAjRoxgXV0DZZETpI+YOnWqn5/f1atXY2Ji3NzcZsyYQUR37tyxs7OLi4uLj49nXWCDxDrZpvGf//wHQNOmTfPz8+/fv+/k5ARgwoQJeDD8Yl1gg2OpE6SP8PX1PXDgwKVLl3Q63aBBg0RR3L9/vyRJoihevnw5ICDAz8+PdY0NDOtkm8zx48cFQbC1tb19+3ZZWZmnpycAeSwvD79YF9iwKKTFAtCyZcszZ86cO3dOr9e/8MILjo6OcXFxeXl5rq6uaWlpLi4u8sQpV0dYJ9uULl26pFar1Wp1SkpKRUVFly5d8KDRkodfrAtsQBQVLCJ69dVXAYwcOZKI9uzZA8DR0bF79+4AFi1axLq6BkRpwcrKyrKxsQGQkJBARAMGDAAQEREhCIK1tfWNGzdYF9hQKC1YRLRw4UIAffr0IaLk5GT5sq1BgwYBePXVV1lX11AoMFiFhYXNmzcHsHPnTiIaN24cgLCwMI1GI4ri999/z7rABkGBwSKiNWvWAPD19TUYDOnp6QMHDkxMTAwJCQHQvn171tU1CBYfrK+/pri46ofR0fTLL1R1sXJMTEzVn06ePKnVarVaLZ/TqgMWH6xBg8jami5frnzo40PnzhERbd682dXV1c3NLTo6evz48Xv37iWiDh06AIiPj2dXb0OhhB+hhw/Hr5dhGzt27L17927duvX2229v3rz5hx9+ANC3b18A8rWmnFkpIVgTJqCwEJs3P3RQpVI9++yzAAoKCgAcPHgQgDzMOnLkCIMqGxglBEsQ8MknmDMHeXkPHZeDJV/pcPHixRs3boSEhAiCkJCQUF5ezqTUhkMJwQIQGIgRI7B06UMH5Xuj3dzc5HUAR44c6ejo6Ofnp9frT506xaTOhkMhwQKwbBm2bUNOTvWR7t27a7XalJQU+efCxMTEGTNm8GFW3VBOsBwdsWxZZW+4bx/0elhbW3fq1MloNPr6+gIQRXH9+vU5OTngwyzzs/hgLV+OqsthJk7Ed9/h3DkMGYLnn4deX9kb3r9/39ramojUavW2bdsEQTh69KjBYGBZt9JZfLC6dIGzMwBIEgYOxNix8PGBiwsOHcKgQejWrReAEydO9OjRgx5c+0BERUVFfJhlVhYfrCqiiJwclJbizBkcOgQ3Nxw/bti16wSAY8eOySvCa7XaJUuWyM+PiopiWa7iMZ6gNZ30dFKrCaC2bYmI0tJoyJC/A5C/EsbExADo0qULEQUFBdnb23/99deMK1Y0S9pL5w9FRWH2bAD44IP8uXMdMjIy+vXrd+3aNQCRkZE6na5v376dOnWqqKjg+/CYHetkm1jXrgRctrNrsWrVKiJKT09v0qSJVqvld67WMaUFKy4u28NjrPz/TFRUFBFdvHjR3t5eEITjx4+zrq4BUUiwqhaWKSkpkdefEUXR1tb21q1bRLRgwQI8uKbU4uj1+jfffNPiVmVSQrDS0tJUKtWAAQO2bdtmMBjkG6DDwsKOHDkiP6GgoKBZs2YAdu3axbbUp3Dnzh0AzZo1Y11I7ShhuuHUqVMajebAgQNjxozx9vaWtxdITU2Vf4ROT0+fNm3am2++CWDOnDlGo5FxubWk1+sBNGrUiHUhtcQ62aZx9+7djz76SL5qtEpSUhI92G0gIiLCy8sLwOeff8662Nq5cOECAD8/P9aF1I5CgiWTJGn//v2jR48WRdHLy2vgwIGSJP33v/+1tbUFMHPmTABubm7FxcWsK62FxMREAIGBgawLqR1FBatKYmKivFfF+vXriejjjz8G4Ozs3LFjRwArVqxgXWAtyL+XW9w3D2UGi4h27NgBwMbGJi0tTZIk+b7CZ555BoCHR7d794ysC3xS8v3cAwcOZF1I7Shh8P5YYWFh48aNKy4unjRpkiRJMTExjo6Ox44d69v3k/v3E99/32Jm3i108K7YYAFYt26du7t7QkLCypUr3dzcVq9eDSAxcUtBgbB2LTIzWdf3ZCw0WIrtCmX79u0TBEGn0509e5aIRo8eDaBp0/0ATZ7Murgnk/vFFwkBARfnzmVdSO0oPFhE9Ne//hVA586dy8rKcnJyXFxcAA+12iiKdOYM6+KexOrVBNDMmazrqB0ld4WyqKgoHx+fM2fOvPfee87OzuvXrweuEf1LkrBwIevinoReDwCW1hUqP1g2NjaxsbEqler999+Pj49//vnnp0yZUlHxrkpVvHs3Dh9mXd8fKikBAGtr1nXUjvKDBaBnz56zZ8+Wd70vKipas2aNl5dDRUUkgHfeQX2/IE0OFm+x6qclS5Z07NgxPT193rx5tra2sbGxKtUa4PbJk/j2W9bF/T65K+QtVv2k0+m2bNliZWX16aef7tmzp3fv3jNnTgWW2Nvv8fUtZV3d7+JjrHrO399fXoZ02rRp9+7dW758uZ/fzwUF//fGG8lVz5k/H6mpDGt8HN4V1n9z587t06fPrVu3Zs2aZWVltXHjRn//KT/99MzevZVPOHjwoXup6wXL7AqVP4/1iPT0dPlih23bthHRSy/R3/9O3t6k1xMRBQfTg6sD6428PMrOJkvb5bphtVgAPD09IyMjAUyfPl2+OLN7d/j54Z//ZF3ZryUloWNH9OqFoUPRti22b2ddUG2wTjYDkiTJe7E+//zzL71Ec+aQRkPW1pSSUp9arOJicnWljRsrH548Sfb2lJrKtKZaaHAtFgBBEGJiYpo0abJr167z58/v2fMfo5H69Km8J7G+OHIETZsiIqLyYVAQwsIsqNFqiMEC0KJFi7Vr1wK4cOHC+fPfzp4d8/33yM7GxYusK6ty9Sp8fB464uuL9HRG1dRaAw0WgPDw8DFjxtja2jZu3Hjp0olqNf71r8qv9vWCrW3l98EqRUWws2NUTa013GAB+Oijj8rK/lZY+OX169cBBAbi+nV07YoNGyBJrIvr0AGnTj2UrSNHEBDArqBaYj3IY0xe2Ojll1+uOjJ8OAG0fDm7mqoMHUphYXThAl29SnPnko8PFRWxrulJKWpRkKeQmZnp4+NTUVGRmprq4+MD4NAhhIZCFHHoEPr0YVpcSQlWrcLPP6O0FN264e230bw504Jqg3Wy2ZsyZQqAqVOnVh2ZN48AatmScnIY1kVEROvW0b59ZDCwrqPWGnqLBSA9Pd3X11cQhMuXL3t4eAAwGvHcc/j5ZwwejN27IbIaiBYVwcEBajUKC6HVMiriKTXowbvMy8srPDzcYDDIM/IA1Gps2QJnZ+zZgw8/ZFdZcjIkCR07WlyqAN4VEhFRWlqaWq3WaDTXr1+vOvjDDySKpFZTSgqjsuSr3S1zj0XeYgGAt7f3mDFjDAbDhzUaqMGD8Y9/YO1atG/PqKzkZADo0oXR6f8c1smuL1JSUkRR1Ol0N2/efORP48bR229XP+zdm/Ly6qSmDh0IoBMn6uRkJsZbrErt27cfNWpUWVnZh78aVaWkICYG8fGVD5OTURdLIZWU4NIlqNWWNClaAw9WtUWLFomiGB0dnZWV9cif5s3Da6+hTrccOHsWRiP8/S3vEj8APFg1+fv7Dx8+vLS0dOXKlY/8KTQUPj6o05XhT58GgK5d6/CUpsSD9ZBFixYJgrBu3bpffvnlkT+tXo2oqLpb8eHn27ev9+xZ2L17HZ3P1HiwHtK5c+dhw4bp9fpVq1Y98qfWrfHWW3jnnTqqZNb333scPXquQ4c6Op/Jsf72UO8kJSUJgmBjY/PLL7/IRzp2pORkIqKyMmrfnkSRcnPNW0NZWZlWqxVFsbCw0LxnMhveYj2qa9eugwYNKi4ultcBBGBvD3kjC60Wa9fCwQGCYN4azp8/X15e7uvrK9/3YYl4sB5j0aJFAD7++OP79+8D+Pnn6q/8/fsjLg4//WTeAk6fPg2gq8WO3MGD9Vg9evQIDQ0tKChYs2aNfKSgoGDlypVEFB+PkBDMmIFSc94+nZycDKCLhc65y1j3xfVUQkICAHt7+1u3bkmS1K7da8CRt97aTERBQQTQ2rVmPHtwcDCAw4cPm/EcZsaD9Zvat28PoF+/fkT04ov/BUgUv0tISPjuOwLI1ZVKSsxyXoPBYG1tLQjC/fv3zXKCOsGD9Zuio6MbN26sVquPHTuWk0MaTSkgNW8+JDc3NzCQAPrf/zXLeeWtX318fMzy7nWFB+v3yBuluLu75+bmzppVARCwfdiwYTt2SAC5u1NZmYnPmJmZ6efn5+7uPmnSJBO/dd3iwfo95eXlPXv2BDB06NCsLMnKSgIkoOPq1Z906kQARUeb8nQ7d+6U9z0AEB4ebsq3rnM8WH8gMzPTyckJwMqVK2fOJIAaNz7UsuXNf/6TAGrVyjSNlsFgWLx4sby9lPxlcOLEiSZ4X3Z4sP7Yrl27BEHQaDRxcYlWViQIEpDfpg317HkrJGTWhg1f/Mn31+v18l7oGo0mKioqNjaWB6uheOONN5ydmw0adGjOnFPe3gHOzuEAde36FYDWrVuX/blW65133gHg5OR09OhRIvriiy8UECw+QfpEIiMju3U7s3dvvzNnmt+4ceX+/a8dHC6fPj3G1bVDRkbGpk2b/sybJyUlAZgwYYK81Y8gCADI0u+eYp1si5GRQU5OBFDPnn8D0K9fhCCQSrUJgJeXl+Fpb/27evWqKIrW1tb37t0jol69eoWGhgKIiIgwafl1jQerFnbtIkEgtTpTo9GqVKqJEy8BxsaN2wGIjY19uveU96uWO774+HgADg4OACZMmGDS2usa7wprYdgwzJoFo9Fdp5tUUVEBfPD556rVq+cDWLZs2VNsClxRUbFx40YAw4YNCwwMHD9+PICQkBCTV84A62RbmLIyCg4mIEMUtSqV6sqVK0ajsW3btgC+/PLL2r7bzp07AbRr1y41NRWAKIqCIERFRQEYP368OeqvM7zFqh2tFlu3Ijy8VXh4hCiKR48eValU8+bNA7B8+fLaNlr//ve/AUybNk2ewZIkqX///s0taOWP38aDVWseHti8GSEhK1q2LA4JeRmAp6enKL517drIqpv0n8SdO3f27Nmj1WojqtaDBF555RXTV8wCD9ZT0mia5OdrXn8dxcVYsGCDJDmUllovWbJEnjt4rJCQkNDQ0MjIyPj4+PLy8g0bNhiNxuHDhzdr1uzixYsAVCrViBEjlDHdoGZdgAUbNAhXrmDkSCQnx/r7p+p0madPGyZOnJiUlGRlZfXIk/Pz8xMSEioqKg4cOADAzs6uoqICQP9evVBWtm3bNgD29vY6ne6hlxHh+nVkZaFdOzg719EHMwUerKcnili+HIMHQ60W+vTxs7PzKSpqm5KSsmzZsmXLlj3yZAcHh8zMzISEhAMHDsTHx6empspt0rlvv8Xs2XMkqTOQptEgL6+6xcrIwAsvwMoKnp44fhy9e+Ozz6DRMPioT4HxlweLFRtL8kxTRAS9+CItWkTz55M8ller1cePH//9l7/wwgsAunfvvnfUKEkQCKj8T63O9fb+CJg6ahT160fz5lW+oLiYevSgDz8088cyGR6sp1QVrNxccnWll16i+fOJiObMmQOgXbt2enkTlcfJzc3V6XQqlSozM5OI+gcHDwA+AE5ZWZFWS0Ax8EpYGAkCFRRUv2zrVurTx8wfy2T44P3PcnLCe+/h668rH7733nv+/v5paWkrV+77rZfExsaWlZUNGTLE3d09NTX14MmTJ+zs3gHGtWyJu3d/nD//daBxSQmcnB5af9vTE9evm/fDmA4P1lPS6WBjU/nvKVMQEgJ5vK7T6TZu3NS584+LFg0/cuTxr/3ss88ATJs2DUB0dDQAuWckItja3gkI+Awo0mpRUPDQsuB5eZY0fmfdZCrT4sUEUJs2D3Vlsp9++gmAi4uLwWAoLS11dnYGIE/Be3l5EdHWrVsBjBs7llxdaf/+6le++Sb97W91+CH+FN5imcXChQgKwvXrj9mfJyYmBsDUqVPVavWOHTtyc3MDAwP9/f1RY+7KByAAkZGYPBmbNuHYMSxdiq++woIFdfox/gQeLLNQq/HFF7Cywvr1+OGH6uP5+fnbt28XBGHy5Ml4ELJXXnnF09OTiNLT0wHk5eXZ+vsHODkhIgKbNiE5GWvWwGjEiRNwc2P0gWqPdZOpZCtWEEAtWtDdu5VHPvnkEwChoaFElJ6eLq8+kp+fX/NVM2bMAPDBBx/UfcEmxFssM/qf/8GzzyIrCzNnVh7ZsGEDHvwguH79eiIaO3asvb19zVfJCzcEBQXVdbmmxTrZCpeWRjY2FBpaedt0QkLC9OnTS0tLDQaDq6srgGPHjtV8vtFotLGxEQThblUrZ5l4sMzuwgVKT6e4uOoj587RqlX7ALRqNavmXs9xcXT6dAoADw+Puq/TtHhXaHb+/jh0CCNG4KuvKo989RX2728cHNz95s1VRUXVzwwPR0JCCix8ASMZD1Yd6d0bc+ciL6/yYVZW1smTJ3/9tAsXLsDSFzACwINVZ3x8MHo05s+vfCiKojxXZTTCYKj8DwoKFr9spu4sXgw/P0yaBFQGCwC6d6/eXaykpDJYCugKebDqjr09PvwQr7+Ofv2qg5WUBEfHyic0akT5+fktWrRwcXFhVqWJ8K6wTr30EmxtsWNHdbBqkiQJiugHwYNV99atw40bvxcsBfSD4MGqG8HBGDWq8t9t22LLFnh6XgUwePChRo2qn+btvQEo4C0W96Q6dsSQIdUPw8LQps1NAD16HKt588S9e+8CxbzF4p6eSqUCUPMG11u3bmVnZzs6OrZq1YpdXSbDg8WGWq0GIN8BJpN/e+7WrZtg7n0v6gQPFhtyi/XrYCmjHwQPFityi1WzK1TCbhQ18GCx8etg8RaLMwE5WKUPduS5e/fujRs3bG1tvb29mdZlMjxYbGRkZADYvXu3/FBeSqRLly6PnTi1RAr5GJZl//798upq2dnZt2/fhuL6QfBgMdG/f38vLy8Ao0ePdnV1LSws3L59OxQ0cgcPFhOiKMp7bRJRZGRkmzZtkpKSWrdu3aZNG9almQy/bIaN7OxsANu2bduyZQsAOzu7jIwMa2tr1nWZDG+x2HBxcVGr1UajsVevXvv375fvhJZqrtRg4Xiw2IiIiLhy5crOnTvj4+MHDBigjOUha+JdITMeHh4eHh7yv6tWTWZakSnxFqteUF6LxYNVL/AWizML5bVYfIxVL3zl5FTi7u7Kg8WZlmt+Pm7cQI3Lsywd7wrrB/mqUQW1WDxY9YN8UQMfvHMmxoPFmQXvCjmz4C0WZxZyi6WgYAlKmpSzYHo9cnLQsiVUKtalmAZvsVjLzsaAAQgIwMSJcHfHwoXKGGnxCVLWJk1C+/bYtw+iiOxs9O0Lb+/K1dksGe8KmcrPh5MT7t6Fg0PlkZgYbN+OvXuZlmUCvCtk6to1NGtWnSoAvr64epVdQSbDg8WUrS1qrscNoKgID29UYaF4sJhq3RqCgOTk6iOHD0MRdxfywTtTGg3mz0dEBD79FB4e2LsXn3+OEydYl2UCfPBeD2zZgu++w+3b8PPDjBkICGBdkAnwYNUD33wDQcCAAWjcmHUpJsODVQ/4+yMlBYmJCAxkXYrJ8GCxptfD3h6iiIKCyv3KFYF/K2QtORkVFejQQUmpAg8We0lJANCtG+s6TIwHizUeLM4sFBosPnhnSq+HgwMEQWEjd/AWi7EzZ2A0wt9fYakCDxZbNy5fLm3bVlLQ9FUVHiyW/nHkiPWVK9GK+NX5ETxYLMmrcHdT3MgdfPDOkF6vd3BwAFBQUKCk1UdlvMVi5uzZs0aj0d/fX3mpAg8WQ6dOnQIQqMSRO3iwGFLwAAs8WAwpO1h88M6Gskfu4Ne8s3Lt2jUrKytPT09Fpgq8xWJIkqScnJzmzZuzLsQseLA4s+CDd84seLA4s+DB4syCB4szCx4szix4sDiz4MHizIIHizOL/we/g8EBGFne9gAAAnR6VFh0cmRraXRQS0wgcmRraXQgMjAyMy4wOS40AAB4nHu/b+09BiDgZ0AAWSBWAOIGRjYGAyDNzMLBoAGimdgcwDQLm0MGiGZmhAmwM4AFmBACEJoZQyWchhqNUIgmj9BImAEzBKetcA9AbcUlzs3AyMDIpMDEnMHEzJLAwqrAyqbAxp7AzpHBxMGZwMmVwcTFzcDFk8DDm8HEy6fAx5/BxC+QICCYwSQolCAkDBQUSRARTWARy2ASE08Ql1CQkGQQl8pgkpJWkJZhkGJKEGXLYBLhTBDmSxBhAdrIxiQlLsbCzMbOwSkiysbKxSnCy8PGLyAoJMwnnsbIAHQNBDPIHss9Y7+BeeeBgF5x+4XX3tinxE44cFFpsr3jx9f2hdKRBxyWzLf7pnHGfvr/hAPbWlr2y4mdsr9wVeoAo++X/Zfy19vbzlY9MCkm6MD0/wb2L7JO7795rvHAESde+4qqp/unfFtz4LTA8b1HnHL3VzcfPSCyTn3/w6oQu33ztxzg81+//9yq+fZfdx47oLvp7v6nFzbZWzN+PaC18vJ+cQ8Wh9h/Sw9crZi4X+nvMfsZPo0Hnogs3X/nOq/DKSODA7uyf+5P64h2uL5Y4wD7B7YDfhcbHfoPbd0fvfH8/tCDCQ7BrM37Xj8q2x82X9hhVdPGfQ0e/vt/LrhuX8p0av+CTob9XfKH7ZZxdR1gExKxW233fd+cRckHzDtf2juvnbn/0cu1+92LWB0i2xr2z9w9zVpbQtTB9H2FXfF1Jns2IQkHDtvd9myNovsyJrI6lD3gOMA/J9i++6+oQ/ib7/uPbORyCONbah8SdH2/+gJXBzEA8g7SFTZkweoAAALgelRYdE1PTCByZGtpdCAyMDIzLjA5LjQAAHicfVVLbhsxDN37FLpABvyJkpZxHBRFERto096h+9wfJSklQ23qiQjN4Imfx0flUvz38/bj70f5+vHtcikF/vM3xih/GAAub8U35fr67fu9vLw/Xz+/vDx+399/FRqFyc7Ys2Of3x9vn1+wvBQ86mgIUJ7q0To224F9IoB0lMrDgL0CO1COiii2wwNl1Azk8NiFA8gHD+LwyIg9A2WFrjCBFav6Dg/gyhlZJ7J1P/9Eh+DgiRzQNSO13A3JDXQia286vVPXkZHNfMKhI6owT7V7wV4ZVN0K6ubT+KiRvSHboD7JEqiYkcN8PsEBo4UrOAZpQPXARltJCBOrNcqHg6DV6VVFtvjoPbK4rEODcZIm0ysh0AalCW0czbMzowW7zQKpbFC2sgyqld0rHaBBkCWAve25yvSKHMQYV1V0cSWw8Y91Qql7YPNKqDxb0SpvZKFO6JBoIR/CUYxBleumPfRm2XeE7jVEi1YzxAvN0D69KtH0WqfqjGqqdVMArnYNIzxyZaNgQlm0beJf3eoQZZn7LkurpsqtBYTOq+kFCKfsO+Iki5G3ASAKZaHICiudxpqFWeAJXVNFIQ0nGGAlwKbxDerdsnb20KZPE8jMxDZbs6jaTFvZFLoygmR2yDnbWkUaLrkpRvWitDhF95iRbQWfsrOW8czOUtc9eJ/BhVcdg0N/dkTbHn1E7SapVbt2ouithdk6+nq/bZfbvO6uj/vtvO78ofNSs5fC59Ulvs4Lyp963kJoS8+rBm218z4RW/28NMTWOG8GsYV5/MUNYppyDENpmCW+cJpZcYOSRhPD1DSB/mrjlQZN3GBL8yRusKexETc40nSIG8pDIB6LMGndX03ISdLGmMk1CVfckCR9ohuqSYfohjQJTgLTkrDQDfUkIHRDIwnFj6R+esaW0pcXXgmfjWBPmCAR6CLKkvH3z/+utr/8Awo8bTmKavO4AAABjnpUWHRTTUlMRVMgcmRraXQgMjAyMy4wOS40AAB4nCWSO5LbQAxEr+JQqiKn8P8UQ+XeQ0yuE+zh3RgrofjUABoNfX427/36u+X71f26t+352Pu7X5/31v2VN37/wXf++fz5ffHyTr5uX1mcF+FVHl7lpNdty5nt4sXWPtQUVJe2KKTKXM808IHOHtfNi9R1aFZdtyzj1sFNFcCaFIO9MqZKKvqhFY05UHm1zFzycGA2g4qWlfSZ4VEP3p2Ex0Axj1pZgWFTw+HWfarQxCgGS3VesoRDZ3S68uC2ikuXKcngUH/wYCq7joEaQyYjDZGRIo0aO+LeY6PDDI2V4rhUixxchHkoKjuBIIn/TVwDaoh78uZKHazRAbVYIoGASzrqVAFVdLoTpWHTOdyxtlD6dMB0H4pxMvNbxnMsTlGE585nhWypkRs5zxHFfLAQHXuKUzywVc7nfGQTLR4BqgJzmGg6EPvzwAyGNws5afBRUuWkiEvMv6gkTrnpmdFYEqtz5DjAPY6DKBGkisp+//4DeN+N3/SyROMAAAAASUVORK5CYII=\" alt=\"Mol\"/></div></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         CPD_ID SC_RDKit_score   ESPSim ShapeSim ID  \\\n",
       "0  CHEMBL426972         0.4272  -0.0106   0.3889      \n",
       "1  CHEMBL519715         0.5138  -0.0258   0.4642      \n",
       "\n",
       "                                              ROMol  \n",
       "0  <rdkit.Chem.rdchem.Mol object at 0x7ae1b5d1a960>  \n",
       "1  <rdkit.Chem.rdchem.Mol object at 0x7ae1b5d1a9d0>  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "active_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e2e36a7d-85b0-42b1-9904-f03a748e4711",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/iwatobipen/miniforge3/envs/lig3dlens/lib/python3.10/site-packages/rdkit/Chem/PandasPatcher.py:132: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "  for col in df_subset.columns[df_subset.applymap(MolFormatter.is_mol).any()]\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "        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>CPD_ID</th>\n",
       "      <th>SC_RDKit_score</th>\n",
       "      <th>ESPSim</th>\n",
       "      <th>ShapeSim</th>\n",
       "      <th>ID</th>\n",
       "      <th>ROMol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ZINC48412316</td>\n",
       "      <td>0.4304</td>\n",
       "      <td>-0.0040</td>\n",
       "      <td>0.4339</td>\n",
       "      <td></td>\n",
       "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ZINC48421039</td>\n",
       "      <td>0.3149</td>\n",
       "      <td>-0.0118</td>\n",
       "      <td>0.3266</td>\n",
       "      <td></td>\n",
       "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         CPD_ID SC_RDKit_score   ESPSim ShapeSim ID  \\\n",
       "0  ZINC48412316         0.4304  -0.0040   0.4339      \n",
       "1  ZINC48421039         0.3149  -0.0118   0.3266      \n",
       "\n",
       "                                              ROMol  \n",
       "0  <rdkit.Chem.rdchem.Mol object at 0x7ae1b5de09e0>  \n",
       "1  <rdkit.Chem.rdchem.Mol object at 0x7ae1b5de0a50>  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decoy_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4dc315b6-95a0-4aae-b9d2-94a684e9fd83",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5bb5381b-1674-4ab6-b577-def671e6c1f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x7ae1b456e6e0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b456e980>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b456f970>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b456fc10>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x7ae1b456ec20>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b456eec0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b456feb0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b4138190>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x7ae1b456e440>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b456f6d0>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x7ae1b456f160>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b4138430>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x7ae1b456f400>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b41386d0>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()\n",
    "plt.boxplot([active_df['ESPSim'].astype(float),decoy_df['ESPSim'].astype(float)], labels=['active', 'decoy'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "704c6294-fa0b-4683-90f5-da9088011884",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x7ae1b3fed360>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fed600>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fee5c0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fee860>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x7ae1b3fed8a0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fedb40>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3feeb00>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3feeda0>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x7ae1b3fecfd0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fee320>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x7ae1b3fedde0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fef040>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x7ae1b3fee080>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3fef2e0>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()\n",
    "plt.boxplot([active_df['ShapeSim'].astype(float),decoy_df['ShapeSim'].astype(float)], labels=['active', 'decoy'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7c89b783-1036-4049-b2c3-706526d4dfd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x7ae1b3c012a0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c01540>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c02500>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c027a0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x7ae1b3c017e0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c01a80>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c02a40>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c02ce0>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x7ae1b3c00fa0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c02260>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x7ae1b3c01d20>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c02f80>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x7ae1b3c01fc0>,\n",
       "  <matplotlib.lines.Line2D at 0x7ae1b3c03220>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HXximCW+EEQBA0HQt+zBkyJBuz54ZPXq0hgwZ4lMO4YlhGgBA0HQ9PqS9vb3bwmYnT570Ltfw1ceMILzQMwIACBqr9f/+m/nqOlHnb59fDuGHdx8AEDQ33HBDQMshNBFGAABBwwRW9AZhBAAQNL1dWZUVWMMbYQQAEDTHjx8PaDmEJu6mAQAETWdnp892UlKShg4dqrNnz/o8q+ar5RBeCCMAgKBpbGz02f7qw/IuVA7hhWEaAEDQVFVVBbQcQhNhBAAAGEUYAQAEjd1uD2g5hCbCCAAgaHo7MZUJrOGNMAIACJrW1taAlkNoIowAAIJm2LBhAS2H0EQYAQAEzfDhwwNaDqGJMAIACJohQ4YEtBxCE4ue4ZJpbW1VTU3NRcu1tbWppaVFMTExioqK+tqyDodD0dHRgWoigACrq6sLaDmEJsIILpmamhrl5OQEtM7y8nJlZWUFtE4AgdPc3BzQcghNhBFcMg6HQ+Xl5RctV11drfz8fBUWFiojI+OidQIYuFwuV0DLITQRRnDJREdH+9WLkZGRQa8HAIQBJrACAILGYrEEtBxCE2EEAAAYRRgBAAQNc0bQG4QRAEDQeDyegJZDaCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAoW19OKi8vV2lpqZxOp1JTU5WXlyeHw3HB8mfPntWrr76qffv2qaWlRQkJCfrud7+r6667rs8NBwAAocHvMLJ3715t3LhRCxcuVEZGhrZt26ZVq1ZpzZo1Gj58eLfyLpdLP//5zxUbG6sf/vCHio+PV1NTky677LKAfAEAAGBw8zuMbN26VbNmzdKMGTMkSQsXLtRHH32knTt3as6cOd3K79ixQy0tLXr66adls335cqNGjepfqwEAQMjwK4y4XC7V1tb6hA6r1aqsrCxVVVX1eM4f/vAHZWRk6MUXX9T+/fsVGxurKVOmaM6cObJae56y0tHRoY6ODu+2xWJRdHS093OEtq732GKx8H4DYYTrPXz5FUaam5vldrsVFxfnsz8uLk51dXU9nnPy5Ek1NjZq6tSp+ulPf6qGhgatX79enZ2d+s53vtPjOSUlJSouLvZujxs3TgUFBUpISPCnuRik6uvrJUkjR45UUlKS4dYAuFS43sNXnyaw+sPj8Sg2NlaLFy+W1WpVenq6PvvsM7311lsXDCNz585Vbm6ud7srLTc2NsrlcgW7yTCsqanJ+7ErmAAIfVzvocdms/WqI8GvMBIbGyur1Sqn0+mz3+l0dust6RIXFyebzeYzJDNmzBg5nU65XC7vPJLz2e122e32HuvzeDz+NBmDUNd77PF4eL+BMML1Hr78WmfEZrMpPT1dlZWV3n1ut1uVlZUaP358j+dMmDBBDQ0Ncrvd3n319fUaMWJEj0EEAACEF78XPcvNzdU777yjXbt26fjx41q/fr3a29s1ffp0SVJRUZE2bdrkLX/rrbeqpaVFv/nNb1RXV6ePPvpIJSUl+ru/+7uAfREAAGDw8rtrIjs7W83NzdqyZYucTqfS0tK0bNky7zBNU1OTz4zokSNH6mc/+5l++9vfaunSpYqPj9e3v/3tHm8DBgAA4cfiGUSDdI2NjT63/CI0HTx4UDk5OSovL1dWVpbp5gDohzFjxvS67IkTJ4LYEphgt9t7NYGVZ9MAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjbKYbAAAY/FpbW1VTU9OvOg4ePOiz7XA4FB0d3a86MTgQRgAA/VZTU6OcnJx+1fHV88vLy5WVldWvOjE4EEYAAP3mcDhUXl7ebb8/AeWr5zscjn63C4MDYQQA0G/R0dE99mK8++67uvnmmy96/rvvvkv4CGNMYAUABI3D4ZDFYvnaMhaLhSAS5ggjAICgOn78+AUDicVi0fHjxy9xizDQEEYAAEF3/Phxvfvuu4qIiJAkRURE6N133yWIQBJhBABwiTgcDm3btk2StG3bNoZm4EUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYZevLSeXl5SotLZXT6VRqaqry8vLkcDh6LLtr1y698MILPvvsdrteeeWVvrw0AAAIMX6Hkb1792rjxo1auHChMjIytG3bNq1atUpr1qzR8OHDezwnOjpav/rVr/rdWAAAEHr8HqbZunWrZs2apRkzZig5OVkLFy5UZGSkdu7cecFzLBaL4uLifP4BAABIfvaMuFwu1dbWas6cOd59VqtVWVlZqqqquuB5bW1tevjhh+XxeDRu3Djde++9Gjt27AXLd3R0qKOjw7ttsVgUHR3t/Ryhres9tlgsvN9AiOH6Rk/8CiPNzc1yu93dejbi4uJUV1fX4zmjR4/WQw89pNTUVJ07d05vvfWWnnjiCT333HO6/PLLezynpKRExcXF3u1x48apoKBACQkJ/jQXg1R9fb0kaeTIkUpKSjLcGgCBxPWNnvRpAqs/xo8fr/Hjx/ts/+AHP9Dvf/973XPPPT2eM3fuXOXm5nq3u9JzY2OjXC5XcBsM45qamrwfu35xAQgNXN/hxWaz9aojwa8wEhsbK6vVKqfT6bPf6XT2eh6IzWbTuHHj1NDQcMEydrtddru9x2Mej6e3zcUg1fUeezwe3m8gxHB9oyd+hRGbzab09HRVVlZq0qRJkiS3263Kykrl5OT0qg63262jR4/q2muv9b+1GNBqa2t19uzZftdTXV3t87E/hg4dqvT09H7XAwAIHr+HaXJzc7V27Vqlp6fL4XCorKxM7e3tmj59uiSpqKhI8fHxmj9/viSpuLhYGRkZSkxM1NmzZ/XWW2+psbFRs2bNCugXArNqa2s1bdq0gNaZn58fkHp2795NIAGAAczvMJKdna3m5mZt2bJFTqdTaWlpWrZsmXeYpqmpyWeGdEtLi37961/L6XR6/0r9+c9/ruTk5IB9ETCvq0eksLBQGRkZ/aqrra1NLS0tiomJUVRUVJ/rqa6uVn5+fkB6awAAwdOnCaw5OTkXHJZZsWKFz/aCBQu0YMGCvrwMBqGMjAxlZWX1qw6LxaKkpCTV19czpgwAYYBn0wAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKJvpBgAABr7a2lqdPXu23/VUV1f7fOyPoUOHKj09vd/1wDzCCADga9XW1mratGkBrTM/Pz8g9ezevZtAEgIIIwCAr9XVI1JYWKiMjIx+1dXW1qaWlhbFxMQoKiqqz/VUV1crPz8/IL01MI8wAgDolYyMDGVlZfWrDovFoqSkJNXX18vj8QSoZRjsmMAKAACMomcEAWMfFq+6c9Jln7X1qx6LpM+tZ9T0aav683dT3bkv2wQAGNgIIwiYhBty9UKNXao5EoDaAlGHXQk35AagHgBAMBFGEDCNH27Vzx+aL0c/J7hZJI1MSFBTY2O/ekZqqqu1+Omtkub3qz0AgOAijCBgOs58ptGXSd+I7/sMeen/T3C7Ypjq3S39muB27rIv2wQAGNiYwAoAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACM6tMKrOXl5SotLZXT6VRqaqry8vLkcDguet7777+vX/3qV/rmN7+pxx57rC8vDQAAQozfPSN79+7Vxo0bNW/ePBUUFCg1NVWrVq3S559//rXnnTp1Si+//LKuvPLKPjcWAACEHr/DyNatWzVr1izNmDFDycnJWrhwoSIjI7Vz584LnuN2u1VYWKi7775bo0aN6leDAQBAaPErjLhcLtXW1iorK+v/KrBalZWVpaqqqgueV1xcrNjYWM2cObPvLQUAACHJrzkjzc3NcrvdiouL89kfFxenurq6Hs85dOiQduzYoV/+8pe9fp2Ojg51dHR4ty0Wi6Kjo72fY2Dr73vUdX4g32t+boDA4PpGMPRpAmtvtba2qrCwUIsXL1ZsbGyvzyspKVFxcbF3e9y4cSooKFBCQkIwmokAqK+vlyQlJCQoKSkpIHUmJib26/xgtAkIR1zfCDa/wkhsbKysVqucTqfPfqfT2a23RJJOnjypxsZGFRQUePd5PB5J0j333KM1a9b0+AM5d+5c5ebmere7Um9jY6NcLpc/TcYl0tjY6P3Y9UuirywWixITE9XQ0OD9eTHdJiCccX2jr2w2W686EvwKIzabTenp6aqsrNSkSZMkfTk5tbKyUjk5Od3Kjx49Ws8++6zPvtdee01tbW1asGCBRo4c2ePr2O122e32Ho/154cXl0ag3iOPxxPQugD0H9c3gsHvYZrc3FytXbtW6enpcjgcKisrU3t7u6ZPny5JKioqUnx8vObPn6/IyEilpKT4nD906FBJ6rYfAACEJ7/DSHZ2tpqbm7VlyxY5nU6lpaVp2bJl3mGapqYmJhMBAIBe69ME1pycnB6HZSRpxYoVX3vuI4880peXBAAAIYpn0wAAAKOCemsvACA02IfFq+6cdNlnbf2qxyLpc+sZNX3aqv5MO60792WbEBoIIwCAi0q4IVcv1NilmiMBqC0QddiVcEPuxYthUCCMICBaW1slSQcPHux3XW1tbWppaVFMTIyioqL6XE91dXW/2wLgS40fbtXPH5ovR0ZGv+qxSBqZkKCmxsZ+9YzUVFdr8dNbJc3vV3swMBBGEBA1NTWSpKVLlxpuSXddt5MD6LuOM59p9GXSN+L7/geC9OWiZ0lXDFO9u6Vf64Ocu+zLNiE0EEYQEF13VzkcDu9zhPqqurpa+fn5KiwsVEY//wobOnSo0tPT+1UHACC4CCMIiK6F7gIpIyPD5wnRAIDQxK29AADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjbKYbAAAY2FpbWyVJBw8e7HddbW1tamlpUUxMjKKiovpcT3V1db/bgoGDMAIA+Fo1NTWSpKVLlxpuSXdDhw413QQEAGEEAPC1cnJyJEkOh0PR0dH9qqu6ulr5+fkqLCxURkZGv+oaOnSo0tPT+1UHBgbCCADga8XHx2v+/PkBrTMjI0NZWVkBrRODFxNYAQCAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYJStLyeVl5ertLRUTqdTqampysvLk8Ph6LFsRUWFSkpK1NDQoM7OTiUmJuqOO+7QTTfd1K+GAwCA0OB3GNm7d682btyohQsXKiMjQ9u2bdOqVau0Zs0aDR8+vFv5mJgY3XXXXRo9erRsNps++ugjvfDCC4qNjdU111wTiK8BAAAMYn4P02zdulWzZs3SjBkzlJycrIULFyoyMlI7d+7ssfxVV12lSZMmKTk5WYmJibrtttuUmpqqQ4cO9bvxAABg8POrZ8Tlcqm2tlZz5szx7rNarcrKylJVVdVFz/d4PKqsrFRdXZ3uu+++C5br6OhQR0eHd9tisSg6Otr7OUJb13tssVh4v4EQw/WNnvgVRpqbm+V2uxUXF+ezPy4uTnV1dRc879y5c1q8eLFcLpesVqseeOABXX311RcsX1JSouLiYu/2uHHjVFBQoISEBH+ai0Gqvr5ekjRy5EglJSUZbg2AQOL6Rk/6NIHVX1FRUVq9erXa2tp08OBBbdy4UVdccYWuuuqqHsvPnTtXubm53u2u9NzY2CiXy3UpmgyDmpqavB+7fnEBCA1c3+HFZrP1qiPBrzASGxsrq9Uqp9Pps9/pdHbrLTmf1WpVYmKiJCktLU0nTpzQG2+8ccEwYrfbZbfbezzm8Xj8aTIGoa732OPx8H4DIYbrGz3xawKrzWZTenq6KisrvfvcbrcqKys1fvz4Xtfjdrt95oQAAIDw5fcwTW5urtauXav09HQ5HA6VlZWpvb1d06dPlyQVFRUpPj5e8+fPl/Tl/I9vfOMbuuKKK9TR0aGPP/5Yu3fv1oMPPhjQLwQAAAxOfoeR7OxsNTc3a8uWLXI6nUpLS9OyZcu8wzRNTU0+M6Tb29u1fv16ffrpp4qMjNSYMWOUn5+v7OzsgH0RAABg8OrTBNacnBzl5OT0eGzFihU+2/fcc4/uueeevrwMAAAIAzybBgAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUTbTDQAADH6tra2qqam5aLnq6mqfj1/H4XAoOjq6323DwEcYwSXDLysgdNXU1CgnJ6fX5fPz8y9apry8XFlZWf1pFgYJi8fj8ZhuRG81Njaqo6PDdDPQRwcPHvTrl1Vv8MsKGBgu9sfGnj179B//8R86efKkd98VV1yhhQsXaurUqT2ewx8bg5/dbldCQsJFyxFGcMn0tmekra1NLS0tiomJUVRU1NeW5ZcVMPCVlZVp0aJFuuWWW/T9739f06dP165du/T8889r+/btWrdunW677TbTzUQQEEYwaFksFiUlJam+vl6D6McTQA86Ozs1ZcoUZWZmasOGDYqIiPBe352dncrLy9Phw4e1Z88eRUREmG4uAqy3YYS7aQAAQVNRUaFjx44pPz9fVqvvfzlWq1VLlizR0aNHVVFRYaiFGAgIIwCAoDl16pQkKTMzs8fjXfu7yiE8EUYAAEEzatQoSdKhQ4d6PN61v6scwhNhBAAQNJMnT9bYsWNVWFgot9vtc8ztdquoqEgpKSmaPHmyoRZiICCMAACCJiIiQk8++aS2b9+uvLw87d+/X2fOnNH+/fuVl5en7du3a/ny5UxeDXN9upumvLxcpaWlcjqdSk1NVV5enhwOR49lt2/frvfee0/Hjh2TJKWnp+vee++9YPmvw9004YG7aYDQU1ZWppUrV3r/L5CklJQULV++nNt6Q1jQbu3du3evioqKtHDhQmVkZGjbtm368MMPtWbNGg0fPrxb+eeff14TJkzQhAkTZLfb9eabb2rfvn167rnnFB8f789LE0bCBGEECE2dnZ3at2+fvvjiC0VGRmrSpEn0iIS4oIWRZcuW6Rvf+IYeeOABSV+O+T300EP69re/rTlz5lz0fLfbre9973vKy8vTzTff7M9LE0bCBGEECF1c3+Glt2HEr2fTuFwu1dbW+oQOq9WqrKwsVVVV9aqO9vZ2uVwuxcTEXLBMR0eHT+iwWCzeVTYtFos/TcYg1PUe814DoYfrGz3xK4w0NzfL7XYrLi7OZ39cXJzq6up6Vccrr7yi+Pj4r32eSElJiYqLi73b48aNU0FBQa/SFUJHYmKi6SYACBKub5zvkj6194033tD777+vFStWKDIy8oLl5s6dq9zcXO92V4JubGyUy+UKejthlsViUWJiohoaGujGBUIM13d4sdlsgR+miY2NldVqldPp9NnvdDq79ZZ81VtvvaU33nhDy5cvV2pq6teWtdvtstvtPR7jhzd8eDwe3m8gRHF943x+rTNis9mUnp6uyspK7z63263KykqNHz/+gue9+eabev31172TXwEAALr4vehZbm6u3nnnHe3atUvHjx/X+vXr1d7erunTp0uSioqKtGnTJm/5N954Q5s3b9ZDDz2kUaNGyel0yul0qq2tLWBfBAAAGLz8njOSnZ2t5uZmbdmyRU6nU2lpaVq2bJl3mKapqclnlvTvf/97uVwuPffccz71zJs3T3fffXf/Wg8AAAa9Pq3AagrrjIQH1iEAQhfXd3jp7TojPJsGAAAYdUlv7e0vm21QNRf9xPsNhC6u7/DQ2/d5UA3TAACA0MMwDQac1tZWPf7442ptbTXdFAABxvWNnhBGMOB4PB799a9/ZXIbEIK4vtETwggAADCKMAIAAIwijGDAsdvtmjdv3gWfTwRg8OL6Rk+4mwYAABhFzwgAADCKMAIAAIwijAAAAKMIIxiw7r77bu3bt890MwBcwIoVK/Sb3/zGdDMQAggjMG7Lli1aunRpt/3r1q3Ttddea6BFAIBLiScVYcCKi4sz3QQAwCVAGEFAfPLJJ3r99dd17NgxWa1WjR8/XgsWLFBiYqIk6dNPP9XLL7+sAwcOyOVyacyYMXrggQd04sQJFRcXS/pyWEaSHn74YU2fPl133323fvzjH2vSpEl64oknlJmZqX/8x3/0vmZzc7MWL16s5cuX62/+5m/U0dGhV199Ve+//77OnTunsWPH6r777tNVV1116b8hQIhpa2vT+vXrVVFRoejoaN1xxx0+x3tz/R06dEivvfaaampqZLfb5XA49OijjyomJkYdHR16+eWXtXfvXrW2tio9PV3f/e535XA45PF49P3vf1/f+ta3NHv2bG99R44c0WOPPabnn3/e+7sGgxNhBAHR1tam3Nxcpaamqq2tTZs3b9azzz6rX/7yl/riiy+0YsUKxcfH6/HHH1dcXJxqa2vl8XiUnZ2to0eP6sCBA1q+fLkk6bLLLutW/9SpU/XWW2/pvvvuk8VikSTt3btXI0aM0JVXXilJevHFF3XixAn98z//s0aMGKF9+/bpX/7lX/Tss88qKSnp0n0zgBD0u9/9Tn/605/02GOPafjw4dq0aZP++te/Ki0tTdLFr78jR47o6aef1owZM7RgwQJFREToj3/8o9xut7f+iooKPfLII0pISNCbb76pVatWqbCwUDExMZoxY4Z27drlE0Z27typK6+8kiASApgzgoC44YYbNHnyZCUmJiotLU0PPfSQjh49quPHj2vPnj1qbm7W0qVLlZmZqcTERGVnZ2v8+PGKjIxUVFSUrFar4uLiFBcXp8jIyG71Z2dn6/Tp0zp06JB33549ezRlyhRZLBY1NTVp165d+sEPfuD95TR79mxlZmZq586dl/JbAYSctrY27dixQ/fff7+ysrKUkpKiJUuWqLOzU5J6df29+eabSk9P14MPPqi0tDSNHTtWOTk5io2NVVtbm95++23df//9uvbaa5WcnKzFixcrMjJSO3bskCRNnz5ddXV1qqmpkSS5XC7t2bNHM2bMMPNNQUDRM4KAqK+v1+bNm1VTU6MzZ854/9ppamrSkSNHlJaWppiYmD7XHxsbq6uvvlq7d+/WlVdeqVOnTqmqqkqLFi2SJB09elRut1uPPvqoz3kul6tfrwtAamhokMvlUkZGhndfTEyMRo8eLal319+RI0d044039lj/yZMn1dnZqQkTJnj32Ww2ORwOHT9+XJIUHx+v6667Tjt27JDD4dAf/vAHuVyuC9aJwYUwgoAoKChQQkKCFi9erBEjRsjj8ehHP/qRXC5Xjz0dfTFt2jS99NJLysvL0549e5SSkqKUlBRJX/7lZrVaVVBQIKvVt8MvKioqIK8PoGe9uf4C8Xtg5syZKioq0oIFC7Rz507deOONGjJkSL/rhXkM06Dfzpw5o7q6Ot11113KyspScnKyzp496z2ekpKiI0eOqKWlpcfzbTabtyfl63zzm9/UF198oU8++UR79uzR1KlTvcfS0tLkdrv1+eefKzEx0ecfd+UA/ZOYmKiIiAhVV1d797W0tKi+vl5S766/1NRUHTx4sMf6r7jiCtlsNh0+fNi7z+Vy6S9/+YuSk5O9+6677joNGTJEb7/9tg4cOKCZM2cG4auFCYQR9NvQoUM1bNgwbd++XQ0NDaqsrNRvf/tb7/GpU6cqLi5Oq1ev1qFDh3Ty5El9+OGHqqqqkiSNGjVKp06d0pEjR9Tc3KyOjo4eXycqKkrXX3+9Nm/erBMnTviEkdGjR2vq1KkqKipSRUWFTp06pZqaGpWUlOijjz4K7jcACHFRUVGaOXOmfve736myslJHjx7VCy+84J1M3pvrb86cOfrLX/6i9evX63//93914sQJvf3222publZUVJRuvfVWvfzyy/rkk090/Phx/frXv1Z7e7tP4LBarZo+fbo2bdqkxMREjR8/3sj3A4HHMA36zWq16tFHH9VLL72kH/3oRxo9erS+973vacWKFZK+7Pl44okntHHjRv3iF7+Q2+1WcnKyHnjgAUnS5MmTVVFRoaeeekpnz5713trbk2nTpukXv/iFrrzySo0cOdLn2MMPP6z/+q//0saNG/XZZ58pNjZWGRkZmjhxYjC/fCAs3H///Wpra1NBQYGioqJ0xx136Ny5c97jF7v+Ro8erSeeeEKvvvqqli1bpsjISDkcDk2ZMkWSNH/+fLndbhUWFqqtrU3p6en62c9+1m3O18yZM1VSUsLE1RBj8Xg8HtONAACgN/785z9r5cqV+vd//3eGYEMIPSMAgAGvo6NDzc3N+s///E/deOONBJEQw5wRAMCA9/777+vhhx/W2bNnfVZiRmhgmAYAABhFzwgAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAw6v8B0zxHErjwz2kAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()\n",
    "plt.boxplot([active_df['SC_RDKit_score'].astype(float),decoy_df['SC_RDKit_score'].astype(float)], labels=['active', 'decoy'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1b32d751-771d-405c-8b37-207ac764ea57",
   "metadata": {},
   "outputs": [],
   "source": [
    "active_df['LABEL'] = 1\n",
    "decoy_df['LABEL'] = 0\n",
    "df = pd.concat([active_df,decoy_df])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6d909dba-cadf-46ce-aa59-de2821630587",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20654, 7)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "34e76605-c807-44a2-a6d9-59170d1d0181",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(338, 7)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "active_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a75f4e2f-0621-4bd2-b998-22915b99dc80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "import matplotlib.pyplot as plt\n",
    "true_values = np.repeat([1, 0], [active_df.shape[0], decoy_df.shape[0]])\n",
    "true_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f1426c2c-7453-4c09-b140-88ba2a63fda6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'True Positive Rate')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sscore = df.sort_values(by='ESPSim', ascending=False)['ESPSim']\n",
    "label =  df.sort_values(by='ESPSim', ascending=False)['LABEL']\n",
    "fpr, tpr, _ = roc_curve(true_values, label)\n",
    "plt.clf()\n",
    "roc_auc = auc(fpr, tpr)\n",
    "lw = 2\n",
    "plt.plot(fpr, tpr, color='darkorange',\n",
    "             lw=lw, label='ROC curve (area = %0.3f)' % roc_auc)\n",
    "plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "46bdc8ed-cc84-4e2d-b96a-caf95d88bc2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "sscore = df.sort_values(by='ShapeSim', ascending=False)['ShapeSim']\n",
    "label =  df.sort_values(by='ShapeSim', ascending=False)['LABEL']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e04701ce-695c-4c2a-9fa4-b477e2126bd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'True Positive Rate')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fpr, tpr, _ = roc_curve(true_values, label)\n",
    "plt.clf()\n",
    "roc_auc = auc(fpr, tpr)\n",
    "lw = 2\n",
    "plt.plot(fpr, tpr, color='darkorange',\n",
    "             lw=lw, label='ROC curve (area = %0.3f)' % roc_auc)\n",
    "plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1394beda-cd62-4386-a83f-278ba4d0be43",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3c55ac39-a265-4d70-a5c4-545ac6a12f47",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30d60519-6ff9-49ca-a20a-2b9e85e41b15",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b937ae3-fd7a-481a-a6cd-9bd50c372f06",
   "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": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}