PAINS-alert.ipynb

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              "ene_six_het_A(483) (6)",
              "hzone_phenol_A(479) (3)",
              "ene_five_het_G(10) (1)",
              "ene_one_ene_A(57) (1)",
              "azo_A(324) (1)",
              "imine_one_isatin(189) (1)",
              "quinone_A(370) (1)",
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            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300>",
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            "_model_name": "SliderStyleModel",
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            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
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        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Jahan08/RDKit-application/blob/main/PAINS-alert.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Strucrural Alert removal"
      ],
      "metadata": {
        "id": "DWfGQg0e_QFi"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        " #### When working in drug design, we often need filters to identify molecules containing functional groups that may be toxic, reactive, or could interfere with an assay. Here we use 8 functional alert sets: Dundee, BMS, Glaxo, Inpharmatica, LINT, PAINS, MLSMR, SureChEMBL"
      ],
      "metadata": {
        "id": "_j1-Ov6kvFxi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install rdkit"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s5BDIzGKwVXe",
        "outputId": "fd9a9311-d502-4035-92e7-53e2b34b7515"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: rdkit in /usr/local/lib/python3.10/dist-packages (2023.3.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from rdkit) (1.22.4)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from rdkit) (8.4.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install useful_rdkit_utils pandas datamol ipywidgets tqdm"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "grhU3DO8reMD",
        "outputId": "92881c02-4f8d-480f-bafb-c07262cd3a6e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install useful_rdkit_utils"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GU4Gzxw4wX-r",
        "outputId": "444ffb30-44e7-4087-8c15-58a99a7a6a3b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oa38_yeNu82k"
      },
      "outputs": [],
      "source": [
        "import useful_rdkit_utils as uru\n",
        "import pandas as pd\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/sdfbrowserexport-EZEQKY4X.csv')\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "3wM8QytNwups",
        "outputId": "87ad0b3f-1179-4601-b3d0-33bdccf418ac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       ABase ID  AB Batch        Library Supplier   Supplier ID  \\\n",
              "0    AB00122949         2      ChemDiv01  ChemDiv     0160-0031   \n",
              "1    AB00123147         2      ChemDiv01  ChemDiv     0368-0011   \n",
              "2    AB00141204         2      ChemDiv01  ChemDiv     3652-0238   \n",
              "3    AB00146016         2      ChemDiv01  ChemDiv     4384-0087   \n",
              "4    AB00389839         7  MLS_FS_2010_2    MLSMR  SMR000072360   \n",
              "..          ...       ...            ...      ...           ...   \n",
              "136  AB01473847         1      ChemDiv01  ChemDiv     K783-5207   \n",
              "137  AB01473863         1      ChemDiv01  ChemDiv     K783-5224   \n",
              "138  AB01473912         1      ChemDiv01  ChemDiv     K783-5413   \n",
              "139  AB01473928         1      ChemDiv01  ChemDiv     K783-6230   \n",
              "140  AB01473957         1      ChemDiv01  ChemDiv     K783-3189   \n",
              "\n",
              "                                                Smiles  \n",
              "0          c1(c(cccc2NC(=O)c3ccccc3Br)c2)sc(c4n1)cccc4  \n",
              "1            [N+](=O)([O-])c1c(Cl)ccc(c1)C(=O)Nc2nncs2  \n",
              "2       N1(c(cc2)ccc2c3ccccc3)C(=O)C(CC1=O)Sc4nnc[nH]4  \n",
              "3    N12C(SC=C1c3ccccc3)=NC(=O)\\C(=C/c(cc4OC)cc(c4O...  \n",
              "4                 Cc1sc(SCCC(Nc2snc(c3ccccc3)n2)=O)nn1  \n",
              "..                                                 ...  \n",
              "136           c1(C(=O)NCc2ccccc2)coc(nc(cccc3)c3n4)c14  \n",
              "137               C(=C/c1ccccc1C)(/Sc(cccc2)c2N3)\\C3=O  \n",
              "138              N1(CCCC1=O)c(cc2)ccc2C(=O)NC3CCCCCCC3  \n",
              "139             C(=C\\c1cccc(C)c1)(/Oc(cccc2)c2N3)\\C3=O  \n",
              "140  S(=O)(=O)(c1cc(C)ccc1C)N(Cc(cc2)ccc2F)c3ccc(cc...  \n",
              "\n",
              "[141 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fcd8a2d7-11f7-4e80-801c-26a3ee14cbb3\" 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>ABase ID</th>\n",
              "      <th>AB Batch</th>\n",
              "      <th>Library</th>\n",
              "      <th>Supplier</th>\n",
              "      <th>Supplier ID</th>\n",
              "      <th>Smiles</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AB00122949</td>\n",
              "      <td>2</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>0160-0031</td>\n",
              "      <td>c1(c(cccc2NC(=O)c3ccccc3Br)c2)sc(c4n1)cccc4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AB00123147</td>\n",
              "      <td>2</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>0368-0011</td>\n",
              "      <td>[N+](=O)([O-])c1c(Cl)ccc(c1)C(=O)Nc2nncs2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AB00141204</td>\n",
              "      <td>2</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>3652-0238</td>\n",
              "      <td>N1(c(cc2)ccc2c3ccccc3)C(=O)C(CC1=O)Sc4nnc[nH]4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>AB00146016</td>\n",
              "      <td>2</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>4384-0087</td>\n",
              "      <td>N12C(SC=C1c3ccccc3)=NC(=O)\\C(=C/c(cc4OC)cc(c4O...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AB00389839</td>\n",
              "      <td>7</td>\n",
              "      <td>MLS_FS_2010_2</td>\n",
              "      <td>MLSMR</td>\n",
              "      <td>SMR000072360</td>\n",
              "      <td>Cc1sc(SCCC(Nc2snc(c3ccccc3)n2)=O)nn1</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>136</th>\n",
              "      <td>AB01473847</td>\n",
              "      <td>1</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>K783-5207</td>\n",
              "      <td>c1(C(=O)NCc2ccccc2)coc(nc(cccc3)c3n4)c14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>AB01473863</td>\n",
              "      <td>1</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>K783-5224</td>\n",
              "      <td>C(=C/c1ccccc1C)(/Sc(cccc2)c2N3)\\C3=O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>AB01473912</td>\n",
              "      <td>1</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>K783-5413</td>\n",
              "      <td>N1(CCCC1=O)c(cc2)ccc2C(=O)NC3CCCCCCC3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>AB01473928</td>\n",
              "      <td>1</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>K783-6230</td>\n",
              "      <td>C(=C\\c1cccc(C)c1)(/Oc(cccc2)c2N3)\\C3=O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>AB01473957</td>\n",
              "      <td>1</td>\n",
              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>K783-3189</td>\n",
              "      <td>S(=O)(=O)(c1cc(C)ccc1C)N(Cc(cc2)ccc2F)c3ccc(cc...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>141 rows × 6 columns</p>\n",
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              "        document.querySelector('#df-fcd8a2d7-11f7-4e80-801c-26a3ee14cbb3 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-fcd8a2d7-11f7-4e80-801c-26a3ee14cbb3');\n",
              "        const dataTable =\n",
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              "                                                    [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",
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              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    border-radius: 50%;\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "      border-right-color: var(--fill-color);\n",
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              "      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",
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              "        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-3bd23a86-aba7-4102-a702-3cf5d3dfe0d6 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import datamol as dm\n",
        "from ipywidgets import interact\n",
        "from tqdm.auto import tqdm\n",
        "from ipywidgets import IntSlider, Dropdown"
      ],
      "metadata": {
        "id": "B3HoZvWQmLId"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "reos_7 = uru.REOS(\"PAINS\")  #optionally specify the rule set to use\n",
        "reos_7.set_output_smarts(True) # the new code\n",
        "df[['rule_set_7','reos_7', 'smarts_7']] = df.Smiles.apply(reos_7.process_smiles).tolist()\n",
        "df\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 547
        },
        "id": "1b1CW1pz-Ja7",
        "outputId": "56edfa72-c859-44e6-bb58-1ebfefa29b99"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       ABase ID  AB Batch        Library Supplier   Supplier ID  \\\n",
              "0    AB00122949         2      ChemDiv01  ChemDiv     0160-0031   \n",
              "1    AB00123147         2      ChemDiv01  ChemDiv     0368-0011   \n",
              "2    AB00141204         2      ChemDiv01  ChemDiv     3652-0238   \n",
              "3    AB00146016         2      ChemDiv01  ChemDiv     4384-0087   \n",
              "4    AB00389839         7  MLS_FS_2010_2    MLSMR  SMR000072360   \n",
              "..          ...       ...            ...      ...           ...   \n",
              "136  AB01473847         1      ChemDiv01  ChemDiv     K783-5207   \n",
              "137  AB01473863         1      ChemDiv01  ChemDiv     K783-5224   \n",
              "138  AB01473912         1      ChemDiv01  ChemDiv     K783-5413   \n",
              "139  AB01473928         1      ChemDiv01  ChemDiv     K783-6230   \n",
              "140  AB01473957         1      ChemDiv01  ChemDiv     K783-3189   \n",
              "\n",
              "                                                Smiles rule_set_7  \\\n",
              "0          c1(c(cccc2NC(=O)c3ccccc3Br)c2)sc(c4n1)cccc4         ok   \n",
              "1            [N+](=O)([O-])c1c(Cl)ccc(c1)C(=O)Nc2nncs2         ok   \n",
              "2       N1(c(cc2)ccc2c3ccccc3)C(=O)C(CC1=O)Sc4nnc[nH]4         ok   \n",
              "3    N12C(SC=C1c3ccccc3)=NC(=O)\\C(=C/c(cc4OC)cc(c4O...      PAINS   \n",
              "4                 Cc1sc(SCCC(Nc2snc(c3ccccc3)n2)=O)nn1         ok   \n",
              "..                                                 ...        ...   \n",
              "136           c1(C(=O)NCc2ccccc2)coc(nc(cccc3)c3n4)c14         ok   \n",
              "137               C(=C/c1ccccc1C)(/Sc(cccc2)c2N3)\\C3=O         ok   \n",
              "138              N1(CCCC1=O)c(cc2)ccc2C(=O)NC3CCCCCCC3         ok   \n",
              "139             C(=C\\c1cccc(C)c1)(/Oc(cccc2)c2N3)\\C3=O         ok   \n",
              "140  S(=O)(=O)(c1cc(C)ccc1C)N(Cc(cc2)ccc2F)c3ccc(cc...         ok   \n",
              "\n",
              "                 reos_7                                           smarts_7  \n",
              "0                    ok                                                 ok  \n",
              "1                    ok                                                 ok  \n",
              "2                    ok                                                 ok  \n",
              "3    ene_six_het_A(483)  [#6]-1(-[#6](~[!#6&!#1]~[#6]-[!#6&!#1]-[#6]-1=...  \n",
              "4                    ok                                                 ok  \n",
              "..                  ...                                                ...  \n",
              "136                  ok                                                 ok  \n",
              "137                  ok                                                 ok  \n",
              "138                  ok                                                 ok  \n",
              "139                  ok                                                 ok  \n",
              "140                  ok                                                 ok  \n",
              "\n",
              "[141 rows x 9 columns]"
            ],
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              "      <td>AB01473847</td>\n",
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              "      <td>c1(C(=O)NCc2ccccc2)coc(nc(cccc3)c3n4)c14</td>\n",
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              "      <th>137</th>\n",
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              "      <td>C(=C/c1ccccc1C)(/Sc(cccc2)c2N3)\\C3=O</td>\n",
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              "    <tr>\n",
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              "      <td>AB01473912</td>\n",
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              "      <td>ChemDiv01</td>\n",
              "      <td>ChemDiv</td>\n",
              "      <td>K783-5413</td>\n",
              "      <td>N1(CCCC1=O)c(cc2)ccc2C(=O)NC3CCCCCCC3</td>\n",
              "      <td>ok</td>\n",
              "      <td>ok</td>\n",
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              "      <td>C(=C\\c1cccc(C)c1)(/Oc(cccc2)c2N3)\\C3=O</td>\n",
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              "<p>141 rows × 9 columns</p>\n",
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              "      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-5d64005f-f28a-45d0-a8a7-99b39bef28fb 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-5d64005f-f28a-45d0-a8a7-99b39bef28fb');\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-392ec022-4ca2-4a86-b7f4-df6046f2f73a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-392ec022-4ca2-4a86-b7f4-df6046f2f73a')\"\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-392ec022-4ca2-4a86-b7f4-df6046f2f73a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### rule_set and reos are added to the dataframe with the name of the rule_set and the name of the rule matched by each molecule. If the molecule doesn't match any rules, both columns contain ok. In the following section we also add smarts column to see the structure of the molecules with structural alerts."
      ],
      "metadata": {
        "id": "Zu9PLYTuoCVR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Summarise the data and put it into a lists taht we will use for the visualization"
      ],
      "metadata": {
        "id": "cmLYZi5XxQxa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "vc = df.query(\"reos_7 != 'ok'\").reos_7.value_counts()\n",
        "rule_freq = vc.reset_index().values.tolist()\n",
        "rule_freq = [(f\"{a} ({b})\",[a,b]) for a,b in rule_freq]"
      ],
      "metadata": {
        "id": "iZvCXvpVrTws"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Set up the interactive visualization: the trick is t set up the observe method on the rule sector, which contains teh rules and the number of molecules matching the rule.  "
      ],
      "metadata": {
        "id": "cbKKDoQxzW7v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rule_selector = Dropdown(layout={'width': 'initial'},options=rule_freq,\n",
        "                         description=\"Rule:\")\n",
        "mol_selector = IntSlider(min=0,max=rule_freq[0][1][1]-1,\n",
        "                        description=\"Molecule:\")\n",
        "\n",
        "def update_slider_range(*args):\n",
        "    mol_selector.max = rule_selector.value[1]-1\n",
        "    mol_selector.value = 0\n",
        "\n",
        "rule_selector.observe(update_slider_range,'value')\n",
        "\n",
        "def foo(x,y):\n",
        "    match_df = df.query(\"reos_7 == @x\")\n",
        "    row = match_df.iloc[y]\n",
        "    return dm.viz.lasso_highlight_image(target_molecules=row.Smiles,search_molecules=row.smarts_7,use_svg=False)\n",
        "interact(foo,x=rule_selector, y=mol_selector);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381,
          "referenced_widgets": [
            "3c95ad1122a5491b9a7ebe13570cbefa",
            "04f75560a0164bff825660c05ee0e101",
            "38b16c7901cd4568b25337afe67b441a",
            "1a139c7666204a9d869f8b2181d60797",
            "c65ead249bfe4056900791936345e0ae",
            "9cdd447f193649debd272abe2ad11395",
            "ff60703ee21f463bbb7e80b08618f762",
            "9f28ace732654e02ba8f5c93ba6394bf",
            "b157966b31f147b3ac7a6c41c9dd2473",
            "edf3ef783eb341399018113b7df7fbee"
          ]
        },
        "id": "K3J6ITX3ydZ_",
        "outputId": "7b9081c6-7908-46af-cf71-3275aae32665"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "interactive(children=(Dropdown(description='Rule:', layout=Layout(width='initial'), options=(('ene_six_het_A(4…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3c95ad1122a5491b9a7ebe13570cbefa"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### This cell is similar to the cell above except that it displays up to 6 molecules and the substructure matching the alert. Use the menu to examine molecules matching the alerts."
      ],
      "metadata": {
        "id": "ydXTrxx627L9"
      }
    }
  ]
}