MLChemTools Python Package
Overview
ChemoBiolysis is a versatile Python package designed for chemical and biological analysis. Whether you are conducting Quantitative Structure-Property Relationship (QSPR) analysis, exploring molecular structures, or performing virtual screening, this package provides a comprehensive set of tools to meet your needs.
Features
QSPR Analysis
Perform QSPR analysis on CSV files.
Calculate molecular descriptors.
Save results and obtain a model summary.
Chemical Assay Exploration
Display active and inactive chemicals based on Assay ID.
Retrieve compound CIDs and sample SIDs by Assay ID.
Molecular Structure Analysis
Perform virtual screening on a file with specified SMILES strings.
Display the maximum common substructure of a list of molecular structures.
Identify and display chiral centers in molecular structures.
Explore bond types, stereochemistry, and more.
Structure Comparison and Visualization
Highlight the differences between two molecular structures.
Draw a list of SMILES representations.
Display Gasteiger charges for a list of molecular structures.
Substructure Analysis
Mark atoms matching a given substructure represented by SMILES.
Check if a substructure is present in a list of compounds.
Delete a specified substructure from a list of compounds.
Installation
bash
Copy code
pip install chemobolysis
Usage
python
Copy code
import chemobolysis
# Example: QSPR Analysis
chemobolysis.qspr_analysis("path/to/csv_file.csv", "dependent_variable_column")
# Example: Virtual Screening
chemobolysis.virtual_screening("path/to/file.txt", "SMILES1", "SMILES2", ...)
# Example: Highlight Difference
chemobolysis.highlight_difference("mol1", "mol2")
For detailed documentation and examples, refer to the ChemoBiolysis Documentation.
Contribution
Contributions are welcome! If you encounter any issues or have suggestions for improvement, please open an issue or submit a pull request.
License
This project is licensed under the MIT License.
Ahmed Alhilal
=============
0.0.1 (27/02/2024)
-------------------
- First Release
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"description": "MLChemTools Python Package\r\nOverview\r\nChemoBiolysis is a versatile Python package designed for chemical and biological analysis. Whether you are conducting Quantitative Structure-Property Relationship (QSPR) analysis, exploring molecular structures, or performing virtual screening, this package provides a comprehensive set of tools to meet your needs.\r\n\r\nFeatures\r\nQSPR Analysis\r\nPerform QSPR analysis on CSV files.\r\nCalculate molecular descriptors.\r\nSave results and obtain a model summary.\r\nChemical Assay Exploration\r\nDisplay active and inactive chemicals based on Assay ID.\r\nRetrieve compound CIDs and sample SIDs by Assay ID.\r\nMolecular Structure Analysis\r\nPerform virtual screening on a file with specified SMILES strings.\r\nDisplay the maximum common substructure of a list of molecular structures.\r\nIdentify and display chiral centers in molecular structures.\r\nExplore bond types, stereochemistry, and more.\r\nStructure Comparison and Visualization\r\nHighlight the differences between two molecular structures.\r\nDraw a list of SMILES representations.\r\nDisplay Gasteiger charges for a list of molecular structures.\r\nSubstructure Analysis\r\nMark atoms matching a given substructure represented by SMILES.\r\nCheck if a substructure is present in a list of compounds.\r\nDelete a specified substructure from a list of compounds.\r\nInstallation\r\nbash\r\nCopy code\r\npip install chemobolysis\r\nUsage\r\npython\r\nCopy code\r\nimport chemobolysis\r\n\r\n# Example: QSPR Analysis\r\nchemobolysis.qspr_analysis(\"path/to/csv_file.csv\", \"dependent_variable_column\")\r\n\r\n# Example: Virtual Screening\r\nchemobolysis.virtual_screening(\"path/to/file.txt\", \"SMILES1\", \"SMILES2\", ...)\r\n\r\n# Example: Highlight Difference\r\nchemobolysis.highlight_difference(\"mol1\", \"mol2\")\r\nFor detailed documentation and examples, refer to the ChemoBiolysis Documentation.\r\n\r\nContribution\r\nContributions are welcome! If you encounter any issues or have suggestions for improvement, please open an issue or submit a pull request.\r\n\r\nLicense\r\nThis project is licensed under the MIT License.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nAhmed Alhilal\r\n=============\r\n\r\n0.0.1 (27/02/2024)\r\n-------------------\r\n- First Release\r\n",
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