medicinal-chemistry

Molecular Processing Made Easy.

The official repository for the book "Machine Learning for Drug Discovery" (Manning Publications)

Open Source, Automated free binding free energy calculation between protein and small molecule. An all-in-one workflow, free energy pertubation with OpenMM.

Implements the blood brain barrier score described in: J. Med. Chem. 2019, 62, 21, 9824-9836 (https://doi.org/10.1021/acs.jmedchem.9b01220)

Nanome Lib - Python API for Nanome Plugins

Auditable generation and multi-objective triage of structurally diverse, drug-like molecules with RDKit.

Open-sourced docking for small molecule to protein target. It prioritizes enhanced user-friendliness and accessibility.

Virtual laboratory for rational drug design and discovery at the blood-brain barrier supervised by Prof. Dr. Sergey Shityakov, MD, PhD.

The goal of this project is to generate a linear regression model that accepts ChEMBL inhibitor data for a target of interest as input and produces inhibitor bioactivity predictions with respect to the specified target as output.

Local and reproducible route auditing for AiZynthFinder, Syntheseus and RENKIN — plus a portable Rust retrosynthesis engine.

Here I provide some code that enables users to calculate CNS MPO score for their molecules, based on the SMILES and known pKa values.

Agent skill for choosing small-molecule design tools for molecular generation, synthesis planning, docking, and property prediction.

Bellerophon: a structure-based tool for automatic PROTAC decomposition

This repository forms the electronic laboratory notebook (ELN)for Klementine Burrell-Sander's PhD's

An exercise in the form of a Jupyter Notebook with describes how to use Python, pandas, and RDkit to enumerate isosteric replacements of a given drug-like chemical structure.

Computational chemistry platform designed to accelerate lead optimization by generating synthetically accessible chemical space.

A single-file, browser-based chemical data platform for medicinal chemistry — SAR, ADME, MPO, kinase selectivity, AI/ML

CuraFrame is a constraint-driven framework for transparent, safety-first reasoning about hypothetical therapeutic designs. It evaluates explicit pharmacological and population-specific limits, making unsafe ideas fail early, clearly, and audibly—without automating discovery.

Integrated cheminformatics platform for molecular descriptor analysis, drug-likeness evaluation, and drug–drug interaction prediction using RDKit, PubChem, and SwissADME validation.

Agentic drug discovery workflows on fully open-source tooling: RDKit, AutoDock Vina/smina, fpocket, ChEMBL. MCP tool servers + Claude agents, with a retrospective validation harness.