morgan_fingerprint.ipynb

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        "<a href=\"https://colab.research.google.com/github/Jahan08/RDKit-application/blob/main/morgan_fingerprint.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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      "source": [
        "!pip install rdkit"
      ],
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        "id": "O0iNYjk42lIa",
        "outputId": "9e5df477-af2f-4388-af2d-d5e210505ea4"
      },
      "execution_count": null,
      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "Collecting rdkit\n",
            "  Downloading rdkit-2023.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (29.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m29.7/29.7 MB\u001b[0m \u001b[31m50.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from rdkit) (1.23.5)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from rdkit) (9.4.0)\n",
            "Installing collected packages: rdkit\n",
            "Successfully installed rdkit-2023.3.3\n"
          ]
        }
      ]
    },
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          "height": 363
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        "outputId": "6294f846-742d-489c-cab3-ab2936a7db33"
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        {
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              "                                              Smiles\n",
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              "3  N12C(C=CC(Cl)=C1)=NC(=CC2=O)COC(=O)c3cc(nc(on4...\n",
              "4    c1(SCC(=O)N(CC2)C2)c(C(OCC)=O)c(C)nc(c3ccco3)n1\n",
              "5  c1(c(ccc(c1)S(C)(=O)=O)NC2CCOc(cccc3)c23)[N+](...\n",
              "6                   N1=C(SCC2CCCCO2)NC(=O)c(ccs3)c13\n",
              "7  S(=O)(=O)(N(CC)CC)N(CCC(=C1)c2c(cccn3)c3[nH]c2)C1\n",
              "8      c(CN(CCC1c2c3c([nH]c2)cccc3)CC1)(n4)n(CCC)nn4\n",
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          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "import rdkit\n",
        "from rdkit.Chem import AllChem\n",
        "import pandas as pd\n",
        "\n",
        "df=pd.read_csv(\"/content/CFF_775k_SD_prepared_noDuplicate.csv\")\n",
        "\n",
        "df.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import random\n",
        "\n",
        "## Provide file name with path for example: \"C:\\Users\\xxxxx\\flights.csv\"\n",
        "split_source_file = input(\"/content/CFF_775k_SD_prepared_noDuplicate.csv\")\n",
        "\n",
        "## find number of lines using Pandas\n",
        "pd_dataframe = pd.read_csv(split_source_file, header=0)\n",
        "number_of_rows = len(pd_dataframe.index) + 1\n",
        "\n",
        "## find number of lines using traditional python\n",
        "# fh = open(split_source_file, 'r')\n",
        "# for count, line in enumerate(fh):\n",
        "#     pass\n",
        "# py_number_of_rows = count\n",
        "\n",
        "print(f\"{number_of_rows}\")\n",
        "\n",
        "## Incase of equal split, provide the same number for min and max\n",
        "min_rows = int(input(\"Minimum Number of rows per file? : \"))\n",
        "max_rows = int(input(\"Maximum Number of rows per file? : \"))\n",
        "\n",
        "file_increment = 1\n",
        "skip_rows = 1\n",
        "\n",
        "## first file random numbers\n",
        "number_of_rows_perfile = random.randint(min_rows, max_rows)\n",
        "\n",
        "while True:\n",
        "\n",
        "    if number_of_rows_perfile <= 0:\n",
        "        break\n",
        "    ## Read CSV file with number of rows and skip respective number of lines\n",
        "    df = pd.read_csv(split_source_file, header=None, nrows = number_of_rows_perfile,skiprows = skip_rows)\n",
        "\n",
        "    ## Target file name\n",
        "    split_target_file = f\"{split_source_file[:-4]}_{file_increment}.csv\"\n",
        "\n",
        "    ## write to csv\n",
        "    df.to_csv(split_target_file, index=False, header=False, mode='a', chunksize=number_of_rows_perfile)\n",
        "\n",
        "    file_increment += 1\n",
        "\n",
        "    skip_rows += number_of_rows_perfile\n",
        "\n",
        "    ## Last file handler\n",
        "    if skip_rows >= number_of_rows:\n",
        "        number_of_rows_perfile = number_of_rows - skip_rows\n",
        "    else:\n",
        "        number_of_rows_perfile = random.randint(min_rows, max_rows)"
      ],
      "metadata": {
        "id": "eXkyGL87SyyE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the molecules\n",
        "mols = [rdkit.Chem.MolFromSmiles(smile) for smile in df['Smiles']]\n",
        "\n",
        "# Create a Morgan fingerprint\n",
        "fp = AllChem.GetMorganFingerprint(mols, 2, 2)\n",
        "\n",
        "# Save the fingerprint to a DataFrame\n",
        "df = pd.DataFrame(fp, columns=['Smiles', 'fp'])\n",
        "\n",
        "# Print the DataFrame\n",
        "print(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AygNtx_C2h9-",
        "outputId": "6582ace9-df3f-4fe6-aac3-7dcb7991cdda"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[19:29:30] Explicit valence for atom # 1 Cl, 2, is greater than permitted\n",
            "[19:29:36] Can't kekulize mol.  Unkekulized atoms: 0\n",
            "[19:29:44] Explicit valence for atom # 2 C, 5, is greater than permitted\n",
            "[19:29:44] Explicit valence for atom # 3 O, 3, is greater than permitted\n",
            "[19:29:58] SMILES Parse Error: syntax error while parsing: N(C(=O)c(c12)n(CC['CL'])cn1)C(N2C)=O\n",
            "[19:29:58] SMILES Parse Error: Failed parsing SMILES 'N(C(=O)c(c12)n(CC['CL'])cn1)C(N2C)=O' for input: 'N(C(=O)c(c12)n(CC['CL'])cn1)C(N2C)=O'\n",
            "[19:29:59] SMILES Parse Error: syntax error while parsing: c1cc2c(cc(c(c2Cc(c(c3cc4C(=O)O)cc['^CH2']c3)c4O)O)C(=O)O)cc1\n",
            "[19:29:59] SMILES Parse Error: Failed parsing SMILES 'c1cc2c(cc(c(c2Cc(c(c3cc4C(=O)O)cc['^CH2']c3)c4O)O)C(=O)O)cc1' for input: 'c1cc2c(cc(c(c2Cc(c(c3cc4C(=O)O)cc['^CH2']c3)c4O)O)C(=O)O)cc1'\n",
            "[19:29:59] Explicit valence for atom # 13 N, 4, is greater than permitted\n",
            "[19:29:59] Explicit valence for atom # 8 Cl, 3, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 7 Cl, 2, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 11 Cl, 2, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 7 Sn, 5, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 5 Cl, 2, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 13 Br, 2, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 5 Cl, 2, is greater than permitted\n",
            "[19:30:00] Explicit valence for atom # 5 Cl, 2, is greater than permitted\n"
          ]
        }
      ]
    }
  ]
}