Standardize_visualize_IUPAC.ipynb

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        "This script will take the input from your csv file, in which the SMILES of the compounds are stored in the **\"SMILES\"** column. The following sequential processed are done:\n",
        "- Sanitize structure (Kekulize, check valencies, set aromaticity, conjugation and hybridization)\n",
        "- Normalize functional groups\n",
        "- Uncharge molecule (not enabled by default)\n",
        "- Get the parent fragment (not enabled by default)\n",
        "- Reionize the molecule (not enabled by default)"
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        "# @title Install prerequisite rdkit, XlsxWriter, STOUT\n",
        "%pip install rdkit chemical-converters XlsxWriter git+https://github.com/Kohulan/Smiles-TO-iUpac-Translator.git"
      ]
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      "source": [
        "# @title Data import\n",
        "from google.colab import drive, files\n",
        "import pandas as pd\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import Draw, PandasTools\n",
        "from IPython.display import HTML, display\n",
        "from rdkit.Chem.rdmolfiles import MolFromSmiles\n",
        "from rdkit.Chem.MolStandardize import rdMolStandardize\n",
        "\n",
        "\n",
        "# Data input\n",
        "print(\"Upload csv file containing the SMILES column\")\n",
        "uploaded = files.upload()\n"
      ],
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        "# @title Standardize process\n",
        "df = pd.read_csv(list(uploaded.keys())[0])\n",
        "pd.set_option('display.max_rows', None)\n",
        "\n",
        "smis = df[\"SMILES\"]\n",
        "uncharger = rdMolStandardize.Uncharger()\n",
        "\n",
        "ms=[]\n",
        "for smi in smis:\n",
        "    m = MolFromSmiles(smi)\n",
        "\n",
        "    # Sanitize\n",
        "    Chem.SanitizeMol(m, sanitizeOps = (Chem.SANITIZE_ALL^Chem.SANITIZE_CLEANUP^Chem.SANITIZE_PROPERTIES))\n",
        "\n",
        "    # Normalize functional groups\n",
        "    cm = rdMolStandardize.Normalize(m)\n",
        "\n",
        "    # Get parent and uncharge\n",
        "    #im = uncharger.uncharge(rdMolStandardize.FragmentParent(cm))\n",
        "\n",
        "    # Reionization (if needed)\n",
        "    #rm = rdMolStandardize.Reionize(im)\n",
        "\n",
        "    # Append to list\n",
        "    ms.append(Chem.MolToSmiles(cm))\n",
        "df[\"SMILES_std\"]=ms\n",
        "PandasTools.AddMoleculeColumnToFrame(df, 'SMILES_std', 'Molecule')"
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            "Downloading trained model to /root/.data/STOUT-V2/models\n"
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            "/root/.data/STOUT-V2/models.zip\n",
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      "source": [
        "# @title IUPAC reading using STOUT (use at your risk as this is based on a LLM model not a systematic one - https://doi.org/10.1186/s13321-021-00512-4)\n",
        "from STOUT import translate_forward\n",
        "iupacs = [translate_forward(SMILES) for SMILES in df[\"SMILES\"]]\n",
        "df[\"IUPAC\"] = iupacs\n",
        "PandasTools.SaveXlsxFromFrame(df, 'SMILES_processed.xlsx', molCol='Molecule')"
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        "After the whole process, the processed file would be appeared as **\"SMILES_processed.xlsx\"**"
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