t002.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mirsadra/DPP-4/blob/main/t002.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rdkit"
      ],
      "metadata": {
        "id": "6GDmxqduGsA5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from pathlib import Path\n",
        "import math\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.lines import Line2D\n",
        "import matplotlib.patches as mpatches\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import Descriptors, Draw, PandasTools"
      ],
      "metadata": {
        "id": "nm1wKd3oGLEY"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S5OO1AKSGKtN",
        "outputId": "cab292f1-0211-464f-d7f9-bbed50153d4e"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls \"/content/drive/My Drive/Colab Notebooks/dpp4\""
      ],
      "metadata": {
        "id": "MfoSv-c-JIYG",
        "outputId": "574caaea-4fe7-4906-b5ab-a966bed44542",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "output_data.csv  t002_dpp4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "file_path = '/content/drive/My Drive/Colab Notebooks/dpp4/output_data.csv'"
      ],
      "metadata": {
        "id": "snmBjvhXJMg9"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "molecules = pd.read_csv(file_path)"
      ],
      "metadata": {
        "id": "bfYWk5deHVfL"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PandasTools.AddMoleculeColumnToFrame(molecules, \"smiles\")"
      ],
      "metadata": {
        "id": "esqWbp_WJPkE"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "molecules"
      ],
      "metadata": {
        "id": "yN0ZuWgdJgoc",
        "outputId": "70527200-b3c5-4b92-920e-042f2895a37e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     molecule_chembl_id          IC50 units  \\\n",
              "0          CHEMBL237119  1.200000e-02    nM   \n",
              "1         CHEMBL4113723  5.000000e-02    nM   \n",
              "2          CHEMBL237336  6.400000e-02    nM   \n",
              "3         CHEMBL4113723  8.000000e-02    nM   \n",
              "4         CHEMBL5269668  9.000000e-02    nM   \n",
              "...                 ...           ...   ...   \n",
              "4396       CHEMBL175260  1.000000e+06    nM   \n",
              "4397       CHEMBL268012  1.800000e+06    nM   \n",
              "4398      CHEMBL4535549  3.830000e+06    nM   \n",
              "4399       CHEMBL276884  9.100000e+06    nM   \n",
              "4400      CHEMBL5276961  1.100000e+09    nM   \n",
              "\n",
              "                                                 smiles      pIC50  \\\n",
              "0     CN(C)C(=O)[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](...  10.920819   \n",
              "1     CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...  10.301030   \n",
              "2     C[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](N)C(=O)N1...  10.193820   \n",
              "3     CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...  10.096910   \n",
              "4     CC#CCN1C(N2CCC[C@@H](N)C2)=NC2C1C(=O)N(Cc1cccn...  10.045757   \n",
              "...                                                 ...        ...   \n",
              "4396                            O=C(CNCc1ccccc1)N1CCCC1   3.000000   \n",
              "4397  Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(Cl)(Cl)Cl)OCC(...   2.744727   \n",
              "4398  CC[C@H](C)[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@@H...   2.416801   \n",
              "4399  Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(F)(F)F)OCC(F)(F)F   2.040959   \n",
              "4400  COc1ccc(S(=O)(=O)Nc2nc(N3CCOCC3)nc(N3CCOCC3)n2...  -0.041393   \n",
              "\n",
              "                                                 ROMol  \n",
              "0     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f9fa7a0>  \n",
              "1     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f9fba70>  \n",
              "2     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f8552a0>  \n",
              "3     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f854dd0>  \n",
              "4     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f854f90>  \n",
              "...                                                ...  \n",
              "4396  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e110>  \n",
              "4397  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e180>  \n",
              "4398  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e1f0>  \n",
              "4399  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e260>  \n",
              "4400  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e2d0>  \n",
              "\n",
              "[4401 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-851d7696-83b5-41da-968d-1e6611f6957c\" class=\"colab-df-container\">\n",
              "    <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>molecule_chembl_id</th>\n",
              "      <th>IC50</th>\n",
              "      <th>units</th>\n",
              "      <th>smiles</th>\n",
              "      <th>pIC50</th>\n",
              "      <th>ROMol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL237119</td>\n",
              "      <td>1.200000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CN(C)C(=O)[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](...</td>\n",
              "      <td>10.920819</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>CHEMBL4113723</td>\n",
              "      <td>5.000000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...</td>\n",
              "      <td>10.301030</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>2</th>\n",
              "      <td>CHEMBL237336</td>\n",
              "      <td>6.400000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](N)C(=O)N1...</td>\n",
              "      <td>10.193820</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>3</th>\n",
              "      <td>CHEMBL4113723</td>\n",
              "      <td>8.000000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...</td>\n",
              "      <td>10.096910</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>4</th>\n",
              "      <td>CHEMBL5269668</td>\n",
              "      <td>9.000000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC#CCN1C(N2CCC[C@@H](N)C2)=NC2C1C(=O)N(Cc1cccn...</td>\n",
              "      <td>10.045757</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>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4396</th>\n",
              "      <td>CHEMBL175260</td>\n",
              "      <td>1.000000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>O=C(CNCc1ccccc1)N1CCCC1</td>\n",
              "      <td>3.000000</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>4397</th>\n",
              "      <td>CHEMBL268012</td>\n",
              "      <td>1.800000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(Cl)(Cl)Cl)OCC(...</td>\n",
              "      <td>2.744727</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>4398</th>\n",
              "      <td>CHEMBL4535549</td>\n",
              "      <td>3.830000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC[C@H](C)[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@@H...</td>\n",
              "      <td>2.416801</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>4399</th>\n",
              "      <td>CHEMBL276884</td>\n",
              "      <td>9.100000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(F)(F)F)OCC(F)(F)F</td>\n",
              "      <td>2.040959</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>4400</th>\n",
              "      <td>CHEMBL5276961</td>\n",
              "      <td>1.100000e+09</td>\n",
              "      <td>nM</td>\n",
              "      <td>COc1ccc(S(=O)(=O)Nc2nc(N3CCOCC3)nc(N3CCOCC3)n2...</td>\n",
              "      <td>-0.041393</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",
              "<p>4401 rows × 6 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-851d7696-83b5-41da-968d-1e6611f6957c')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-851d7696-83b5-41da-968d-1e6611f6957c button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-851d7696-83b5-41da-968d-1e6611f6957c');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-df57e2e4-3762-4baf-a72d-c324ec2652f9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-df57e2e4-3762-4baf-a72d-c324ec2652f9')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "molecules",
              "summary": "{\n  \"name\": \"molecules\",\n  \"rows\": 4401,\n  \"fields\": [\n    {\n      \"column\": \"molecule_chembl_id\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3773,\n        \"samples\": [\n          \"CHEMBL3806023\",\n          \"CHEMBL4535549\",\n          \"CHEMBL3945052\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IC50\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16581815.440211155,\n        \"min\": 0.012,\n        \"max\": 1100000000.0,\n        \"num_unique_values\": 1310,\n        \"samples\": [\n          376.0,\n          4590.0,\n          33.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"units\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"nM\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"smiles\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3773,\n        \"samples\": [\n          \"Cc1nnc2ncc3c(n12)CN([C@H]1CC[C@H](c2cc(F)c(F)cc2F)[C@@H](N)C1)C3\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pIC50\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.323812421736282,\n        \"min\": -0.0413926851582253,\n        \"max\": 10.920818753952377,\n        \"num_unique_values\": 1310,\n        \"samples\": [\n          6.424812155072339\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ROMol\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4401,\n        \"samples\": [\n          \"<rdkit.Chem.rdchem.Mol object at 0x7c3d0f85c5f0>\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate and plot molecular properties for Ro5\n",
        "molecules[\"molecular_weight\"] = molecules[\"ROMol\"].apply(Descriptors.ExactMolWt)\n",
        "molecules[\"n_hba\"] = molecules[\"ROMol\"].apply(Descriptors.NumHAcceptors)\n",
        "molecules[\"n_hbd\"] = molecules[\"ROMol\"].apply(Descriptors.NumHDonors)\n",
        "molecules[\"logp\"] = molecules[\"ROMol\"].apply(Descriptors.MolLogP)\n",
        "molecules[\"n_rotatable\"] = molecules[\"ROMol\"].apply(Descriptors.NumRotatableBonds)\n",
        "molecules[\"n_aromatic_rings\"] = molecules[\"ROMol\"].apply(Descriptors.NumAromaticRings)\n",
        "\n",
        "# Colors are used for plotting the molecules later\n",
        "# molecules[\"color\"] = [\"red\", \"green\", \"blue\", \"cyan\"]\n",
        "# NBVAL_CHECK_OUTPUT\n",
        "molecules[[\"molecular_weight\", \"n_hba\", \"n_hbd\", \"logp\", \"n_rotatable\", \"n_aromatic_rings\"]]"
      ],
      "metadata": {
        "id": "oqZYKseSJkvI",
        "outputId": "fbb26f19-d39a-4f55-8e66-9df8516b0cd7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      molecular_weight  n_hba  n_hbd     logp  n_rotatable  n_aromatic_rings\n",
              "0           401.191483      3      1  2.56220            5                 2\n",
              "1           481.169622     10      1  1.64460            4                 4\n",
              "2           344.170020      2      1  3.49390            4                 2\n",
              "3           481.169622     10      1  1.64460            4                 4\n",
              "4           536.239670     10      1  0.99706            5                 2\n",
              "...                ...    ...    ...      ...          ...               ...\n",
              "4396        218.141913      2      1  1.39860            4                 1\n",
              "4397        543.898038      5      1  5.07540            6                 0\n",
              "4398        721.473812      8      6  1.13530           19                 0\n",
              "4399        448.075341      5      1  3.45960            6                 0\n",
              "4400        436.152889     10      1  0.35420            6                 2\n",
              "\n",
              "[4401 rows x 6 columns]"
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"molecules[[\\\"molecular_weight\\\", \\\"n_hba\\\", \\\"n_hbd\\\", \\\"logp\\\", \\\"n_rotatable\\\", \\\"n_aromatic_rings\\\"]]\",\n  \"rows\": 4401,\n  \"fields\": [\n    {\n      \"column\": \"molecular_weight\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 101.44235872594611,\n        \"min\": 129.10144535199998,\n        \"max\": 1173.68967796,\n        \"num_unique_values\": 2741,\n        \"samples\": [\n          279.11831854,\n          313.17902697600005,\n          450.1934871640001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_hba\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 17,\n        \"num_unique_values\": 16,\n        \"samples\": [\n          3,\n          10,\n          9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_hbd\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 10,\n        \"num_unique_values\": 11,\n        \"samples\": [\n          4,\n          1,\n          9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"logp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4596405438674867,\n        \"min\": -3.4492299999999974,\n        \"max\": 12.047299999999984,\n        \"num_unique_values\": 3128,\n        \"samples\": [\n          1.4793999999999996,\n          1.4544,\n          -1.2585999999999988\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_rotatable\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 33,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          5,\n          33,\n          14\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_aromatic_rings\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 5,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          2,\n          4,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "molecules"
      ],
      "metadata": {
        "id": "olaDBgULJ7f6",
        "outputId": "fac81513-4419-4ae5-e556-c8ae2e928a64",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     molecule_chembl_id          IC50 units  \\\n",
              "0          CHEMBL237119  1.200000e-02    nM   \n",
              "1         CHEMBL4113723  5.000000e-02    nM   \n",
              "2          CHEMBL237336  6.400000e-02    nM   \n",
              "3         CHEMBL4113723  8.000000e-02    nM   \n",
              "4         CHEMBL5269668  9.000000e-02    nM   \n",
              "...                 ...           ...   ...   \n",
              "4396       CHEMBL175260  1.000000e+06    nM   \n",
              "4397       CHEMBL268012  1.800000e+06    nM   \n",
              "4398      CHEMBL4535549  3.830000e+06    nM   \n",
              "4399       CHEMBL276884  9.100000e+06    nM   \n",
              "4400      CHEMBL5276961  1.100000e+09    nM   \n",
              "\n",
              "                                                 smiles      pIC50  \\\n",
              "0     CN(C)C(=O)[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](...  10.920819   \n",
              "1     CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...  10.301030   \n",
              "2     C[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](N)C(=O)N1...  10.193820   \n",
              "3     CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...  10.096910   \n",
              "4     CC#CCN1C(N2CCC[C@@H](N)C2)=NC2C1C(=O)N(Cc1cccn...  10.045757   \n",
              "...                                                 ...        ...   \n",
              "4396                            O=C(CNCc1ccccc1)N1CCCC1   3.000000   \n",
              "4397  Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(Cl)(Cl)Cl)OCC(...   2.744727   \n",
              "4398  CC[C@H](C)[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@@H...   2.416801   \n",
              "4399  Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(F)(F)F)OCC(F)(F)F   2.040959   \n",
              "4400  COc1ccc(S(=O)(=O)Nc2nc(N3CCOCC3)nc(N3CCOCC3)n2...  -0.041393   \n",
              "\n",
              "                                                 ROMol  molecular_weight  \\\n",
              "0     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f9fa7a0>        401.191483   \n",
              "1     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f9fba70>        481.169622   \n",
              "2     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f8552a0>        344.170020   \n",
              "3     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f854dd0>        481.169622   \n",
              "4     <rdkit.Chem.rdchem.Mol object at 0x7c3d0f854f90>        536.239670   \n",
              "...                                                ...               ...   \n",
              "4396  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e110>        218.141913   \n",
              "4397  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e180>        543.898038   \n",
              "4398  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e1f0>        721.473812   \n",
              "4399  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e260>        448.075341   \n",
              "4400  <rdkit.Chem.rdchem.Mol object at 0x7c3d0f71e2d0>        436.152889   \n",
              "\n",
              "      n_hba  n_hbd     logp  n_rotatable  n_aromatic_rings  \n",
              "0         3      1  2.56220            5                 2  \n",
              "1        10      1  1.64460            4                 4  \n",
              "2         2      1  3.49390            4                 2  \n",
              "3        10      1  1.64460            4                 4  \n",
              "4        10      1  0.99706            5                 2  \n",
              "...     ...    ...      ...          ...               ...  \n",
              "4396      2      1  1.39860            4                 1  \n",
              "4397      5      1  5.07540            6                 0  \n",
              "4398      8      6  1.13530           19                 0  \n",
              "4399      5      1  3.45960            6                 0  \n",
              "4400     10      1  0.35420            6                 2  \n",
              "\n",
              "[4401 rows x 12 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-cf266229-c0cd-402d-885f-9d9426c13fbe\" class=\"colab-df-container\">\n",
              "    <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",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>IC50</th>\n",
              "      <th>units</th>\n",
              "      <th>smiles</th>\n",
              "      <th>pIC50</th>\n",
              "      <th>ROMol</th>\n",
              "      <th>molecular_weight</th>\n",
              "      <th>n_hba</th>\n",
              "      <th>n_hbd</th>\n",
              "      <th>logp</th>\n",
              "      <th>n_rotatable</th>\n",
              "      <th>n_aromatic_rings</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL237119</td>\n",
              "      <td>1.200000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CN(C)C(=O)[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](...</td>\n",
              "      <td>10.920819</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",
              "      <td>401.191483</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2.56220</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL4113723</td>\n",
              "      <td>5.000000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...</td>\n",
              "      <td>10.301030</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",
              "      <td>481.169622</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>1.64460</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL237336</td>\n",
              "      <td>6.400000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>C[C@@H](c1ccc(-c2ccc(F)cc2)cc1)[C@H](N)C(=O)N1...</td>\n",
              "      <td>10.193820</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",
              "      <td>344.170020</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3.49390</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL4113723</td>\n",
              "      <td>8.000000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC#CCn1c(N2CCC[C@@H](N)C2)nc2c1c(=O)n(Cc1nc3cc...</td>\n",
              "      <td>10.096910</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",
              "      <td>481.169622</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>1.64460</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL5269668</td>\n",
              "      <td>9.000000e-02</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC#CCN1C(N2CCC[C@@H](N)C2)=NC2C1C(=O)N(Cc1cccn...</td>\n",
              "      <td>10.045757</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",
              "      <td>536.239670</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>0.99706</td>\n",
              "      <td>5</td>\n",
              "      <td>2</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4396</th>\n",
              "      <td>CHEMBL175260</td>\n",
              "      <td>1.000000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>O=C(CNCc1ccccc1)N1CCCC1</td>\n",
              "      <td>3.000000</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",
              "      <td>218.141913</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1.39860</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4397</th>\n",
              "      <td>CHEMBL268012</td>\n",
              "      <td>1.800000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(Cl)(Cl)Cl)OCC(...</td>\n",
              "      <td>2.744727</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",
              "      <td>543.898038</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>5.07540</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4398</th>\n",
              "      <td>CHEMBL4535549</td>\n",
              "      <td>3.830000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>CC[C@H](C)[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@@H...</td>\n",
              "      <td>2.416801</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+gvaeTAAAdiklEQVR4nO2deVzU1d7HPzMMs7DE7haQQiIKiuEaoqIpPq5oVyy7aqbGTTHNq1euuaVlpmmit0wzEyvNjTK1ckEMUCtJXB6XVMipEFGRRZZhGOD7/HEITQVmfjNnhutz3i9fvhDPOd8DfPid3znf5ciICAKBpZHbegKCRxMhLAEXhLAEXBDCEnBBCEvABSEsAReEsARcEMIScEEIS8AFISwBF4SwBFwQwhJwQQhLwAUhLAEXhLAEXBDCEnBBCEvABSEsAReEsARcEMIScEEIS8AFISwBF4SwBFwQwhJwQQhLwAUhLAEXhLAEXBDCEnBBCEvABSEsAReEsARcEMIScEEIS8AFISwBF4SwBFwQwhJwQQhLwAUhLAEXhLAEXBDCEnBBCEvABSEsAReEsARcEMIScEEIS8AFISwBF4SwBFwQwhJwQQhLwAUhLAEXhLAEXBDCEnBBCEvABSEsAReEsHjxzjvvTJgw4fvvv7f1RGwECSxNdXX1woULAdjZ2dnb28fFxZWXl9t6UtZGCMvCFBUVDR48GIC9vX27du1kMhmAoKCg48eP23pqVkUIy5JkZma2a9cOgLu7++HDh4koLS0tMDAQgEwmi4mJKSoqsvUcrYQQlsVISUnx8vICEBwcnJWVVft5nU63cOFCpVIJoHnz5omJiTacpNUQwrIM69evt7e3BzBo0KDCwsIHG5w9e7Zbt27svXbIkCHZ2dnWn6Q1EcIyF4PBMHXqVLbYxcXFVVVV1dWyqqpq/fr1zs7OAFxdXdetW1dP4/92Hh1hVVZWWv8xkJeXFxERAUCtVn/66afGdNFqtQMHDmSPrtGjR/Oeoa14RIR18eLFwMDALl26VFdXW81obm6uu7s7AG9v759//tmkvnFxcQBatGjBaW425xE5IG3ZsmVxcXF6evrXX39tNaMHDhyQyWQODg4nTpzo1KmTSX1dXV0BDB06lM/UbM8jIiy1Wj1nzhwA8+bNq66uto7RAQMG3Llzp6KigohM7ZucnAygb9++HObVOLD1I9NiVFRU+Pn5AdiyZYvVjD777LMAli5dalIvvV7v6Ogok8lyc3M5TczmPDrCIqJPPvkEQOvWrQ0Gg3UsfvvttwD8/PxMerc7cuQIgJCQEH4TszmPyFLIGDduXNu2ba9cubJ582brWBwwYICvry9RQFraTeN7PfrrIB6hpZCxbds2AL6+vlbz+777br5MRi+8YEKXsLAwAPv27eM2KdvzqAmrurq6Y8eOANasWWMdi3/8QXZ2pFLRrVtGtS8uLra3t1coFI+23/CRWgoByGSyRYsWAXjzzTdLSkqsYNHbG5GR0OuxdatR7VNTUw0GQ5cuXR577DHOU7Mlj5qwAAwbNqx79+63bt364IMPrGNx4kQA2LDBqMaHDx8G8Mwzz/Ccke2RkelnMI2fpKSk/v37Ozo6jho1ysvLS61WOzg4uLq6ajQajUbj5uamVqvZB+wz7LhSMgYDoqLwt7/hpZdQXg4Hh/oaP/XUU6dPn05OTu7Tp485Rhs5CltPgAudOnVydnZ+7LHHNm3a1GBjOzu7oqIiR0dHyebs7RERgStXIJfj9dcxfz4KClBUhIICFBaiouJobu6JoqKioqKi7OzsM2fOqFSq7t27Szb3X8GjKaxZs2YVFxe3bNly/vz5hYWFOp1Op9Pd+0FZWZlOp7t161ZOTk5VVdX8+fPfe+89M43a2eHUKQAIC8Ply3c/37v3npSUd2v/6eTkxJ6dZppr5DyCwkpJSdm0aZNKpdq+fXvbtm3rbxwbG7tu3bqkpKTKykqFwqzvxpQpWLQIGg18fVFZCTc3uLjA1RVt2vR66imDy58oFIoFCxasXr16+vTp5phr7Nh6W2physvLWSjwW2+9ZWT79u3b29vbb9q0yRy7y5ZRbi6lplKfPg03zsnJcXR03LZtmzkWGzmPmrBYOEr79u2Zb9gYEhMTXVxcevXqJdnozJn09tvETmSvXjWqy4YNG5RKZXJysmSjjRzbCKusrKykpMTiw545c8be3l4ulx87dsykjoMGDXJ1dT158qQEoykpJJORSkWXL5vWsVevXkql8ocffpBgtPFjA2Fdu3ata9euw4cPt2xgbmVlZefOnQFMnz7d1L7Xr19v1arVyJEjTe1YXk5t2xJAb7xhalcqKSlxdnZWq9Vnz541tk9pKV27ZrIlW2ADYV26dMnNzQ3AggULLDjsihUrAPj6+t65c0dC90WLFjVt2jQvL8+kXnPnEkBt2pBOJ8EmHT16VKlUurm5Xa7rcVdaSj//TJ9+Svv2UWoqzZxJGzbQjBlSjFkX2yyFBw8eVCgUMpnsiy++sMiAWq3WyckJwJ49e6SNUFVV1bZt21mzZhnf5ezZs716veThkWfiwvsXpk2bplKpfHx8fv3115KSkvT09M2bN8fFxeVOmkR+fiSXE0AADRxIr7xC7Bm/aBE1+iQfm728r1y5EoBGo0lPTzd/tMjISAAvmBRj8AA//PCDp6dnZWWlMY0rKytZOtf06SZo8UGqqqo6d+6s0Wjs7e1Z2jTjTK9eBJBCQU88QSEh1KfPXWEtXkx//GGOUStgy13hyy+/DKBFixbXzHtvuHr1qpeXl4eHx40bN8yc0siRIz/77DNjWsbHx7PJFxQUmGn0ypUrTZo0kclkMpnsiSeeCAkJCQ0N3dinDzk51TyuAJLJaO9emjOHtm6ladPMtGgFbOkrNBgM/fr1S01NDQsLS05OVqlUkoe6ffv2hQsXevbsaeaUTp8+3bdvX0dHx6ZNmz7Upcg+KCwsXLhwoU6n27FjR3R0tJlGAQwdOnTfvn33fmZaSMjqM2fg6YngYLRti6AgjB2LqircvImAANzzbGuk2FbXubm5Pj4+AF588UXbzoQxfPhwI/Utl8sBrFq1yiJ2g4ODAbi4uPTp02fKlClr1679MSXF2AivRontoxtOnz4dHh5eWloaHx9vWy/Hrl27oqOjnZyctm/f3qRJk1qXYlFRUe0HpaWlGRkZx48fd3R0LC0t9fLyysrKYsnNkvnpp5+6d+/epEmT7Oxslqf/KGBrZRMRJSYmymQyOzu7b775xlZzKCwsfPzxxwF8+OGH9bfU6/WtWrUCwByRb7/9tpmmJ0+eDGDmzJlmjtMAv/1G779PBw7wtfInjUJYRDR//nwATk5O5r8LS2P27PUAwsPDjTm23bBhAwBvb28Abm5uxWbMWaej//mflT4+rUw4JpVASQmNH0/5+fTZZ/T55xwN/UljEZZer1cqlUql0iYFyr7/nuzsqG/fsxcuXDCmvcFgaN26NYCZ4eGFISE0b55k09u3E0CdO5tXGeDYMdqyhW7frrNBejp9/DERUXU1vfKKWbaMo7GEJu/fv7+ioqJVq1ZPP/20lU3r9Zg8GVVV6N27fYNhNgyFQrFuyZJbnTqtyMpyOXsW8fG4aUL6170kJADAiy+ascv77DNcvowuXTB9OiorH96maVNkZwPA9evw8pJuy3isIF5jYCnFy5Yts77p118ngAIDybSEsaoqCgkhgIKDCaB//lOC6WvXyM6OlErz9n+1T6BVq+iXX+ps9sEHtHgx/etfdOsWpaXR2LFk3FGwNBqFsPLy8lQqlZ2dnZknpRLIzSW1muRykrICf/klAeTlRXI5qdUSTsOXLiWATPd9/5UZM4i5R+fMIWOOiNevp6ZNCSCe24VGIazVq1cDGDRoEG9DrNaQTkfnztHx41RWRtXVtHUrrVwpdcRu3QigkBByc6Pvvqu/bXZ2ja86M5Py8kirpdu3acECSkuTap2IsrIoM5Nee40WLyZjUikTEgggHx9SKgmgDRvMsF0fjUJYoaGhALZv3y59iJIS2rePzpypv9XUqUREubm0eDFNmEBvvUUGA5nid36AAwfIyYnmzaPz5+nsWap3R7lqFWVm1kxj/34KDye9nl57zQzr1dXk708tWtDs2XTxolFdysqoc2cCasJ9VKoKPgFhtn95P3fuXEZGhru7+7BhwyQOUVWF2Fg0b47UVHzxRT0NtVosWYLVqwHA1RUKBS5ckGizhshI/PYbgoOxbx8uXcKMGfU3T0hAfDyysgBgxAisWWOe9bQ0ZGXBYMDy5ejTB1VVDXfRaJCYiKZNcfEiQkJ+Dw3tOHr0H3/80UCvGzcwbx4WLMD+/bh8GYcOAcDOnfVsWWwvLJahNXr0aLVaLXEIrRZBQQgNxdSpSEmpp2HLlpg7F7XH+6+9hvffl2jzLu7uSE7G7NkYORIqFYqK6mn73HN4+WW0bAkAQUG4cwcN/kzrg9U+8fEBgLFjYWdnVC9fX+zaBY3mOxeXgYWFF7TaESNGlJWVPbxxaSl+/x3LlmHWLCxejC+/RF4ecnIAQKtFeXldRmwsrMrKyq1btwJ48cUXpY/i7IyCAgDQ6aBU1tPQxQUA7Ozg7Ax3d6hUGDkSbm4wGKQbBwAiMM9YRQXq9cloNHB0vCuAf/0LFy/CYKiZvmmUlmLnTgDIzASAsWNN6BsefmTDhkGpqZlZWd7e3idPnhw3bhwRsYCwMzt2IC4OQ4bAzw/Ozhg9GjodWE5vixa4cwd792LJEiQn12eCx/pqPKyyY7t27aQPoddTXh4tX06LFtH06fXttx9GWhp17EhLlki3T0R0+DDNnEkrVkgY6PZteuYZ6tHDxMMOol927DD4+FBAAAHUpYupdomIeWbd3NxYDXovLy8WEDaNHaOwP0olhYfTG2/Q+fNUXk7jxtGPP1JCAhHR8uX02291DW5jYY0YMQLA8uXLpQ+xaxcplTRuHO3dS6bXW0tNJYBcXSk/X/oUiIj0enpYefcGuX6dfHwIoPHjTevYt29fuUw2o2fPzPBwfUP+zYdiMBj69+8PoDbAUKlUtm/f/p8vvUSLF9OuXXTxYs23VK+n99+nN9+krCzKzqZTp4iI0tLq+ZJtIyy9Xp+dnX3s2DGlUimTyX6rW/gNM2QIAdShAwEUHy9hgL59CTDHK2MuGRnk4ECAUccFDK1WK5fL1Wq1nZ2dUqm8JfWANT8/n4V0jxo16pdffrFgJUSOwjp9+nRiYuLKlSunTJny/PPPjxgxom/fvqGhoc2aNVMqlQEBARMmTGABJxMnTpRoIzeX7O3J3p6USlIoKCdHwhgnTpBMRk5ORh0ucuKLL0gmo8BAXVJSijHt33jjDQCsElh0dLRku0ygGo3G4r5/jsJqyTY/AAC1Wu3v7x8RERETE3Pw4MGysjLWJiMjg1XjiJf0sKHly+8+roYMkTzVYcOqwsK2Llwo+ZzUAixb9oeTU3N3d/crV67U3zI/P59F+LRo0QKAObFGTKB///vfJY9QFxyF1a1bt9atWz/zzDOxsbEpKSl6vf6hzXbt2iU5GCsnKorkcvLzI4B27pQ81dOn/5f94trwipvq6moW5dymTZt7nx+FhYU///wzS90ZMmSIn58feyVif3t6ekpev6qrq/39/QEcOnTIQl/EXTgKKy8vz8ived68eWx7Umd63cNIT08H0C8g4HDv3rqQEJO3VX9l1KhRACZPnmzOIGZSXFzcvn17AP7+/lOnTu3Xr1/z5s0f3Mg7ODiEhoay3MwWLVpIy6MkInb7q7e3t5GJSSbRKFw61dXV7Od63y9r/cTGxgJgV0JMZc4aM7h06RJLdXRxcfH19Q0ICOjUqdPG8eNp4ECKjqaJEyk2luLiqKSENm+mN9+k1FQzLT6Uq1evenp6Ku85jVMqle3atYuOjl64cOGOHTvOnTvHdHDnzp2goCAAUVFR0nLKX3rpJQDz+GxbGoWwiKi4uLhDhw4AIiMjjfkF0uv1np6ebC0AYJHkxPHjx8v+mv2yvkePuyc67M+mTfT110REM2Zwyho9evRoVFTUokWL9u3b9+uvv9ZTQf7y5cvsMp8VK0xO02UJ/gB+MfHkz0gai7CISKvVNmnSBIAx6cgsOJitFEFBQRaZQHZ2dps2bZiknJ2dPTw8PunVi/z9qU0batuWOnakTp1o5kwqLiYi+uqrBsMZrMDBgwcjItbJZGRqTaSEhAQA4eHhfObVmIRFRGlpaWwV+JjF0f5Jfn5+Wlra+vXrp02b1q9fv2bNmrEfPyuV9u6775pv+ubNm0QUGhp6b629fb17/+Vx5eRE69YRCwd4882aWAWLkpeXN3fuXJO6xMcTQGo1/fSTCb3YbXgbuIXN2D796z42bdo0YcIEpVL5/PPPq9XqCxcuXLhwIT8//75mrq6uXl5emZmZRLR27VqW6GIOYWFh/v7+CQkJdnZ2AFhdSXV5uVt+PnQ6lJejoABEGD4cq1ahshJPPIExY8w0+lDKysoc6q+P+wD/+Ac++gjNmyM9HY8/3nB7rVbr7++vUqlycnLMLOxbJ5wEaw4TJ068r2qji4tLp06dxo4d+8477+zZsycrK4u9eaxZswaAWq3+yaTf1odRWlpq8xJ7Op1O2n2Lej317Ek+PmRkpg/bKg0dOlSCLSNpjMLS6XQ+Pj69e/devXr1oUOH6o9XjomJARAQEHjtmsQ9s06nO8WcX7Zm5cqVQ0w/5mWO1qNHKSGBJkwgrZZycqj2BrQvvqDr1+nq1avvv/8+EcXHx58+fXr8+PEKhaJNmzZ1HS6aj+WEVVVFKSlkiXDELVu29OjRw8jGer1+xIixTz75v927SyxSdfLkyZCQEH7fYpMwtUAX/RkWe/IkbdxIU6bQ1Kmk1dJ779X87+DB9PXXpNVq2REd23GfO3eOnd2PN9X1bTSWe8eKi0PfvigpwcWLmDfPnJECAgImTZo0e/ZsI9vfvo1u3ZCVhbFj8emnUixWV1ezWgw25MqVK08++aTM9GofERHo3x/XryM0FBcu4OmnkZODysqaaNZDh+DtjQez2morG6xZs+bVV1+1xFfwVywm0dokpH/8w5xh1q37xtnZV6vVmtTr/Hl67DECyNQAnD179pSWlprWhw/h4eFt27aVcAh+7xOL5d288MLdJ1Y91DrTvv32W1ONNojlhDVp0v0fSKJDB4Ozs5S6t19+STIZ9etXf0LD/diwWsSDmPrrxGCVl2/coHPn6PBhIqKrV+nECaP6zp07F4C7u7tJzjRjsNxSuHUrzp9HZSV69UJEBBYvxoIFMPEeka++wvPPIywMR45ImcJ338HTE0lJmDMHH36I+44gior0RUU3iv4kOzt75MiRHh4eUixxoLy8XHrUv1SI6Lnnntu5c2dgYOCPP/7owmK3LTW0xWBbZa22Jnbub38jEzfPTZqQSkXmlPJPSqIhQ+jkSXrtNVqwgEJCqGVLcnMjgHr0+OzeL1ypVDo5ORVKCvu0OMePH/f29k5KSrK+6VrP94ABA4xZiCsqKrKyshpsZunjhitXyMuL3NxqXnkWLjS+69q15OxMPj711bZokKQk+vprmjiRpk2jSZP+cmzes+e33t7eQUFBYWFhAwcOZHFgmzdvlm7MctQuSQ0GY/GA1doEEBcX99AGOp0uOTk5NjZ2wIABQUFBfn5+DY5paWFVVdXECj/xBCkUZIoT64MPqEsXaWkBd0lKom++obQ0atWKMjMpI4Oysig//yEvXhs3bgTQs2dPs+xZiKqqKpZWGRgYaJOHaK0zrdbJU1JSsnfv3gkTJvTs2dPPz6+20KFcLm/SpElOQ8G6HA5I79yhoCACKCiosmnTV0JDGww9yM6mDz4gItq9m7Ky6OBBIqK0tHpyQOrk+HFi68nGjQ20LCkpYXecnj9/3mQzHDB1SbI4a9euZW8Izz33XOvWrdVqdbNmzbp27RoZGRkVFTV27NjZs2evXbv28OHDxnzH+Jy8X75Mbm4lQUHDu3YF4OvrW0894/JySk+np5+mkydp7lw6d66mksLGjSThCpI33jAhM4Kd2ptU250rDS5JXNHr9SqVyt7efsuWLfnmJi1xc+nkJyd7OjnJZDJWcSosLIxdK6/T6TIyMrZsMcyZQyNGUOvWZGdHy5bRxx/TxIk0Zw6dO0cDB9Jbb9Gzz0oRVs+eBNDu3UY1PnHiBABPT0+rXXnfIKmpqWxJ2tjgI9fS7Nq1C0D79u0tMhpHXyGrhK5SqVgQrb+//5NPPsliB/z8Lta+UysUNGsWbdpER4+Sv79ZT6zSUlKpyM7OhCRBluiyY8cO0yzxhF1lrVarf/zxR2vaHTp0KCxXB5qvE3rSpEm4Jx8SgEKhCAwMnDr1h/nzads2OnOG9HrKzq4pT/Xee3TtWk38XEoKmXpeuH8/AdS1qwld/vOf/wCIjIw0zRJnXnnlFQDNmjX7o46aWwUFBcePH9+wYcOMGTMiIyNTUoxKGquH3Nxce3t7hUKRm5tr5lAMvsKqqKhgeSDNmzffvn372bNnufp633nnVHDwnddfN+HovbCw0MHBQSaTZXKI2pNMRUUFu4o8NDS0tLS0rkSdWlZKL/BVw7vvvgtg+PDhFpk/WSFshu10du3axdsQEbHEioNsV2k0Y8aMgaWvIjOfW7dusaLfbOt6HxqNJjQ0dMyYMUuXLt29e3eDm/8GYQkHX331lUUmT7yFlZGRAcDDw8MKb8cFBQUs39zUKza5ZkGZQ0JCgkajkcvldSXqWAqWSOfh4WHB9YSvsFg9k2lWuVQoMTERQEREhIS+LGnbUu+tloKlZ7366quWvTH0QaZOnQrgNbOKC94PxyAkg8FggdpXRnP48GEA7NXEJI4dO3bz5k2WCc1hXhIpLS1l+//Y2FiusWIVFRXbtm2DxX9MFhTpfXz55ZcAgoOD+Zm4l0GDBikUiuDgYJMS5T766CN2btStWzfzb6WzILzTs2rZuXMngKeeesqyw3IUFnN+mb9hMZItW7aw91yNRrNs2bIGs/srKyvZlfcAYmJiLFjBxyKwRy+/9KxaBg8eDMlFWeqGl7Bu3LjBzkWuX7/OycSD5Ofnx8TEsK14hw4dTtQd7Xb79u1+/foBUKlUn3zyidVmaCT8qgvdR3l5OStRZvHTFl7CYjfzDhs2jNP49fD9998HBAQAUCgU06ZNK2aJy/dw6dKlwMBAAF5eXuYfLfKAVRcaM2aMFWyxq6YGDx5s2S0CL2GFhIQASExM5DR+/ZSVlcXFxTH3UatWrQ7cc5fad999x+IkO3bsaFYlQW5wrS70IJw83xYW1u+//37gwAG2T7bO8VU9nDp1qnPnzuwtKjo6+ubNm/Hx8Uxto0aNaiQ5FA9y5MgRWPdcjYfnu05h5eXR3r1ERCkpVBuJumULHTtGRDXRw1ot7d9PK1bQxIk0YsTr90ZMu7q6Dhw40FKzlIzBYFi6dCk7R2CXl8rl8iVLlkhLOLYO48ePB7fqQnVhcc93ncL67beaVKqEhLspH//+N8XEkF5P06eTh8dfAn979FgHwNPTMyIiYvLkyatWrWo8B9lZWVm9e/dWKBQODg4W9FrwgHd1oXpo0PNtEn8pkXAfycmoqMCpU2jX7u4nY2KwZg1kMjRvDrn87hXr7dsPDQx81ss6d+GZiJ+fX3Jy8rFjx7y9vZkDrtGSnp5uMBjCw8NrCypZjTVr1ly6dOnIkSNRUVFpaWmmFia5n7oUd98TS6cjg4H+/W/S62nBAho/nkz0yAmMJT8/38iLXi3O7du32b4hOjrazLcFO7azfZDqalRXw98f5eVo1gwnT2LfPgQHIzAQXbuioABWvwn1/wsajcZWD36NRtO/f//PP/88IyNDo9GEh4dLH8tIARYUmJXuJ/gvYvfu3XK5XC6X72XbN0kY691csQLu7tLlK/gvIioqavHixf7+/mxZlEajq+gnaAwQUWlpKbsNRRpCWAIu2P4iTMEjiRCWgAtCWAIuCGEJuCCEJeCCEJaAC0JYAi4IYQm4IIQl4IIQloALQlgCLghhCbgghCXgghCWgAtCWAIuCGEJuCCEJeCCEJaAC0JYAi4IYQm4IIQl4IIQloALQlgCLghhCbgghCXgghCWgAtCWAIuCGEJuCCEJeCCEJaAC0JYAi4IYQm4IIQl4IIQloALQlgCLghhCbgghCXgghCWgAtCWAIuCGEJuCCEJeCCEJaAC0JYAi4IYQm4IIQl4IIQloALQlgCLghhCbgghCXgghCWgAtCWAIuCGEJuCCEJeCCEJaAC/8HYNperY1qlVMAAAMXelRYdHJka2l0UEtMIHJka2l0IDIwMjMuMDkuNgAAeJzNkmtIVEEUx8+dvbvuuqm77uqqqTu6PiZTW9OQQNvZCO1FoCCSkpUfLMPqQ0R9qCit0MKCxPIBQUVpUmQPK0zdWclIkSIopAeZfTArRIuSiLDuPUtKBUHfGhjOb84953/mnDsTPZdfgrKCYHalKztD2fslHWxQrKTxWUJ0VPUTSZ758NPhB5sV0BAlhakg63329xRFA63mN21J868Ks9bPF6j570pLf5vLjALeYTbjj5nPnH8V0PuUJckIkpIPRCNLRAZZKxOtjur8GNHpQW+QicEf/I3gPwf0ARAQSAODGDEFypLJDOZgCLaAxQrWEBoSykiIDWxhshQWDuERED4XbJEQGUWjohmxR8nEToHGQEwsxDrAEUfj4hmJS4CERFlKZJTNY4QlQdJ8SEiG5BRZSk6F1AUgO8GZxohzIbWawGEHK1HurDWZgy1WLbU7YmNs2xSPNPPyIqjJvcN6UqiHitfg3g6lyEN5Bncp1SNPTlN346NJj8p57BNvG96FbH9wl8P6ZuTe/As8undjt8oNabe44doll8r0w1Y++amxR+Wd6at5YfYzjLfVH+SO3EzUr6zYxBvqqpFXTFzntccTkTd9dfKylmLUsdzO52/6TVzlrJsNfM8BilzkDeElH4uQO96l8LPjzcin/Ttdb/s6kDtHTy6pXXkKue9GoSswswD5BAvKbs2TkV8NLna9qcjCWtqCO56rZ/XoDxsxCPvTdcjZ98sFSypF3vL9iFjV7qtV1nVM9C4zIwcXm8X8zyWo82X5gCey/z32PtzW0t3O/LB345MwYel+gVxa895T35WL/bJxl2hZW4mcW14tekgecvrF3eJ6+hjGTz1sEtV9iR7fbGvE5U4X1mJJA2L4XBn6p/XPhbbGInz/Qutt4g7knO1Wb47zGsZozgR4W+le9EeuiffaKw4jHzo/JuBb1RKVn383esve5WapfOXekIjwPMZaxqVTQludgf3WVRF3qHsY4weOjvJFMYMYc8kZ4R7Zl4oc+gN8i+bPB8PtnAAABFJ6VFh0TU9MIHJka2l0IDIwMjMuMDkuNgAAeJx9V8tuJDcMvPsr9AMjiA9R1CGHtb1ZBMGOgWSTf8g9/48U1WN120tkxkN0C9XsUvElP5X4/PH6+z//lv3h16enUtr//M05y9/SWnv6XuKiPH/99tu9vPz48vy+8vL21/3Hn6VT6Yxn8P2I/fLj7fv7CpWXMmtrw2WUm1ZzvMBKw1J8zkcZQK+tdx6z3KR2IR4jAcoCdmf1Vm5ciW2mQAWQsGzMCiRVd5L03R3IUY3nZCq3Vqc598yllXuxSr2RUXhkktjXz8ABj73SHNY4PGJfRBnQyxuAIzajharoJJcEN+FQ6qDhuhwiQth2AqS2kDSb6eI4ms4cGbHRSiqEmENJNxkpSeLl06jP6RFFNm85UtbGIfm0FR0jiJ4iFVpyHdZ5bdi7N852Tn29nCc06niCjSUHGrTUOgbiHcDexmwpMKLDVQTxNrhWpqYp0BcQomhHPlUfPLpnwAgPVe2iOmP/iGabWZZHdBo2o4NnkOXhcJ0ACfJAFeXIIAFZiu0nQF4eGzIHBclI96GuGVAgT8Mb+3COC7GWRoajcJA4atKF4ZLgW1KSEZoowa5iGkoaUij1aYFECiHaOkqUt3gaRY7gIMUELoeH6HhmpG/3A6mGDPeVGdOZM+SEmODJg47q8tEmZ4GM7hZ7RzJKX4UG752yUApBzyhtJ7cZV9G6LIuR8KGTuDdkZBQlUpSzTYkcBFwb4RaSETdPIy96eEVNRg5BiTaQf1nspR9SoXYcWQKvbH3MTCuJHgcAfApiEVRI0b4z6CNUaIHuFgpY75IWiESfi6hSs5WdSNKp6fujlG4G5DBdTmdrUzKn6Or3gLoi430J3Drn0Oh1N6/CiOeC9h6By6AcVCeSZZAtAWRymylUDq/Q1NuaWjP6fAqNdnfDOEIh97GixdHCU+yK1gCDxi0ij5I9avYnpB0EBlr8kXnE3FLkOGQdKpGCVM2QVynSj7cb9mJR/g5g7nOuUYz90CplVGzeR5Gdbxiw3LRbTLmO9mcpMGpqVhPzVafmZJwl9Nf764djxnHweH67v54Hj/jyebzATZHzEEH4oYB+/fYLnQeGWOznqQAHHIz8wOwHDYtWxjnnGT8/pznhdp5Dm+LXPrqgRS7m72US0zKbLvFj5XxKDmd6GaC0zCaMSclhyC4jkWLcxQy97jSWltnMKaiH2eQp2MPwdXhRGN5+eGmMv1NnZMwymzgH8VjZzDmYw/AnVhyKw/Dmz8EfhrfgPB4rmzn7w9tmzsEcRq5tncvq2ZfuTdGX5VNwhB/r58rKFUG7vTReCiNbeQnmMLKZSzCHkc1cIldgZDOXYB4rm7kEcxhtnzIzlNdoY5eGxmF0K6/BPFY2cw3mMLqZqz78b+YazGHUPr3RHuubv4byMLr5q68K0U0fDYHD9Gvl01rZjvsjZWg77vyQam8lqvtay3H//g8Irp/+A/nZYdGojp60AAACRXpUWHRTTUlMRVMgcmRraXQgMjAyMy4wOS42AAB4nJVTuY4UUQz8FcJd6e2T74MWElITEC0REeI7NtmPp/yGI0YaaXpqyna5yn3fP+7PX38+3c+P79f76dO338/3Dfh+/gsB4/u+X/l/OP+a3q9/fqMCn8G+fXh/6k2UZevFdvS6apO71HrR7cp4AOIlBkQ2SzQQpk0hsl54V7GtK3dINwDaHSWe64rNThzDEVb0v3xzZwwHE5ijBsrpzFutGb91Jx8ttJUoOgfiprDpk+Trss2mMmIqNGUIMWNsSxTJ9IS0jmEEH3WyM2Yl2uWg6NRIz2BBkaAbumaKOACn7ClR7dal24Tp0YPTfNmuFGxx8TZXABhXZLwuQk9LaVDAKB+kTAKaFN3YehDCpk4zmSKhAFDCrxKoSw1SrIxVLdQVJAYdesd6N43RE6EoQzyzk6+JSVF+wQEFpUYi/sqDWJCfLftQ8JTMx4mknnAxC56oj+VDZqichIorqgdFqw4/xVp1chBzOaVlxDqnwkLVh9NdUIXRlGp2RMDjgWB6+JiLJ3BUz/2wUR1WaT4Ghrv6A1OmGLVwqm1GBiCEeQ6NqI8TARk2AyCQXGZmbRULHsjh9lQ2VkeEM1Nb+JDKcSAjrHGQZyOapB7XhLcCSKKMJhyElKdRQU3jMmESi9AxLIApzjhCzjZ4H9Ay4HwdoBBf8rRBQgQq3hghAwP242pwT70D4c2yURzY4nm9ff+IwBbPq7QE9tnS2kbLJti3Lx/xtbDFUuzE778AvtLhbFeiBEMAAAAASUVORK5CYII=\" alt=\"Mol\"/></div></td>\n",
              "      <td>721.473812</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>1.13530</td>\n",
              "      <td>19</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4399</th>\n",
              "      <td>CHEMBL276884</td>\n",
              "      <td>9.100000e+06</td>\n",
              "      <td>nM</td>\n",
              "      <td>Cl.O=C(C1CCCN1)N1CCCC1P(=O)(OCC(F)(F)F)OCC(F)(F)F</td>\n",
              "      <td>2.040959</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",
              "      <td>448.075341</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3.45960</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4400</th>\n",
              "      <td>CHEMBL5276961</td>\n",
              "      <td>1.100000e+09</td>\n",
              "      <td>nM</td>\n",
              "      <td>COc1ccc(S(=O)(=O)Nc2nc(N3CCOCC3)nc(N3CCOCC3)n2...</td>\n",
              "      <td>-0.041393</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",
              "      <td>436.152889</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>0.35420</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4401 rows × 12 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cf266229-c0cd-402d-885f-9d9426c13fbe')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-cf266229-c0cd-402d-885f-9d9426c13fbe button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-cf266229-c0cd-402d-885f-9d9426c13fbe');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-e42a23f7-504f-4afa-9d5e-d1e81dacaf07\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e42a23f7-504f-4afa-9d5e-d1e81dacaf07')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e42a23f7-504f-4afa-9d5e-d1e81dacaf07 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_d923f89f-f756-4a7e-8224-135770665822\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('molecules')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_d923f89f-f756-4a7e-8224-135770665822 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('molecules');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "molecules",
              "summary": "{\n  \"name\": \"molecules\",\n  \"rows\": 4401,\n  \"fields\": [\n    {\n      \"column\": \"molecule_chembl_id\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3773,\n        \"samples\": [\n          \"CHEMBL3806023\",\n          \"CHEMBL4535549\",\n          \"CHEMBL3945052\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IC50\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16581815.440211155,\n        \"min\": 0.012,\n        \"max\": 1100000000.0,\n        \"num_unique_values\": 1310,\n        \"samples\": [\n          376.0,\n          4590.0,\n          33.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"units\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"nM\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"smiles\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3773,\n        \"samples\": [\n          \"Cc1nnc2ncc3c(n12)CN([C@H]1CC[C@H](c2cc(F)c(F)cc2F)[C@@H](N)C1)C3\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pIC50\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.323812421736282,\n        \"min\": -0.0413926851582253,\n        \"max\": 10.920818753952377,\n        \"num_unique_values\": 1310,\n        \"samples\": [\n          6.424812155072339\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ROMol\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4401,\n        \"samples\": [\n          \"<rdkit.Chem.rdchem.Mol object at 0x7c3d0f85c5f0>\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"molecular_weight\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 101.44235872594611,\n        \"min\": 129.10144535199998,\n        \"max\": 1173.68967796,\n        \"num_unique_values\": 2741,\n        \"samples\": [\n          279.11831854\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_hba\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 17,\n        \"num_unique_values\": 16,\n        \"samples\": [\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_hbd\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 10,\n        \"num_unique_values\": 11,\n        \"samples\": [\n          4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"logp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4596405438674867,\n        \"min\": -3.4492299999999974,\n        \"max\": 12.047299999999984,\n        \"num_unique_values\": 3128,\n        \"samples\": [\n          1.4793999999999996\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_rotatable\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 33,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"n_aromatic_rings\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 5,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot the molecule properties as bar plots\n",
        "ro5_properties = {\n",
        "    \"molecular_weight\": (500, \"molecular weight (Da)\"),\n",
        "    \"n_hba\": (10, \"# HBA\"),\n",
        "    \"n_hbd\": (5, \"# HBD\"),\n",
        "    \"logp\": (5, \"logP\"),\n",
        "}"
      ],
      "metadata": {
        "id": "IJvhxrBrQwBj"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Start 1x4 plot frame\n",
        "fig, axes = plt.subplots(figsize=(12, 4), nrows=1, ncols=4)\n",
        "\n",
        "# Create subplots\n",
        "for index, (key, (threshold, title)) in enumerate(ro5_properties.items()):\n",
        "    # Using the index of DataFrame as x-values\n",
        "    x = np.arange(len(molecules))\n",
        "    axes[index].bar(x, molecules[key], color='skyblue')\n",
        "    axes[index].axhline(y=threshold, color=\"red\", linestyle=\"dashed\")\n",
        "    axes[index].set_title(title)\n",
        "    axes[index].set_xticks([])  # Optionally, you can add x-ticks as labels if needed\n",
        "\n",
        "# Generate legend elements based on molecule CHEMBL IDs\n",
        "legend_elements = [mpatches.Patch(color='skyblue', label='Molecular Property')]\n",
        "legend_elements.append(Line2D([0], [0], color=\"red\", ls=\"dashed\", label=\"Threshold\"))\n",
        "\n",
        "# Add legend\n",
        "fig.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(1.05, 1))\n",
        "\n",
        "# Adjust layout to fit subplots and legend within the figure canvas\n",
        "plt.tight_layout(rect=[0, 0, 0.85, 1])  # Adjust the rect to make space for the legend\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "HkhaDMdNR_wC",
        "outputId": "79455488-5826-4e84-c0a3-88c8856ed9fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        }
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x400 with 4 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# For More: https://projects.volkamerlab.org/teachopencadd/talktorials/T002_compound_adme.html"
      ],
      "metadata": {
        "id": "HMUxIxOESF98"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "name": "Welcome To Colab",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}