molML/chemical-language-processing-for-bioactivity-prediction

The official codebase for the paper "A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction"

27
/ 100
Experimental

This project helps chemists and drug discovery scientists predict if a small molecule will bind to a target protein, a critical step in drug development. You provide a dataset of molecules, represented as SMILES or SELFIES strings, along with their known binding activity. The project then trains a model that can predict the bioactivity (binding or inhibition) of new molecules, outputting scores or classifications.

No commits in the last 6 months.

Use this if you need to quickly train and evaluate deep learning models for predicting small molecule bioactivity, experimenting with different molecule representations or model architectures.

Not ideal if you prefer a graphical user interface or a solution that doesn't require writing Python code.

drug-discovery cheminformatics molecular-modeling bioactivity-prediction medicinal-chemistry
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 14 / 25

How are scores calculated?

Stars

11

Forks

3

Language

Python

License

Last pushed

Mar 26, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/molML/chemical-language-processing-for-bioactivity-prediction"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.