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MolMiner

MolMiner python jupyter scikit-learn pytorch Keras License: MIT

MolMiner consolidates tools for small-molecule virtual screening. It includes custom scripts for data preprocessing, molecular docking (Autodock Vina), and ML/DL model development (Scikit-Learn and Keras). Using MolMiner is optional and was created to streamline environment setup without manually sourcing relevant Python project packages.

Installation

MolMiner installs a light cheminformatics core by default. Additional modules can be installed if needed.

pip install MolMiner

Additional modules

Install Adds Usage
pip install MolMiner rdkit, pandas, datamol, scikit-learn, splito, umap-learn, matplotlib/seaborn fingerprints, BRICS/RECAP fragmentation, molecule drawing, chemical space (PCA/t-SNE/UMAP), clustering, plots, ROC/PR curves
pip install "MolMiner[ml]" torch, keras, xgboost, optuna mminer.models, mminer.hyperparams
pip install "MolMiner[docking]" prolif, meeko mminer.docking interaction analysis and ligand prep, requires Autodock Vina installation using Conda or Pixi
pip install "MolMiner[safe]" safe-mol, transformers slicer='safe', SAFEbuild, Draw.safe_highlight, Matching
pip install "MolMiner[all]" all of the above everything except AutoDock Vina (see below)

Installing additional modules at once: pip install "MolMiner[ml,safe]".

Using a feature whose extra is missing reports what to install rather than failing with a bare ModuleNotFoundError:

Molecular Docking

Vina is not included in [all], because it cannot be installed by pip on every platform. Installation of Vina should be done directly using Conda or Pixi before the associated MolMiner modules can be used.

Quickstart

Tutorials will be forthcoming.

Metadata

Release files for MolMiner 0.0.3

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Table of built distributions (wheels) for MolMiner 0.0.3
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molminer-0.0.3-py3-none-any.whl Python 3 none any Details for molminer-0.0.3-py3-none-any.whl

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