chemprop/chemprop

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2480 stars · 759 forks observed · 2026-10-10

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Chemprop is a Python package implementing message passing neural networks (MPNNs) for predicting molecular and reaction properties. It provides both a Python API and a command-line interface for training, evaluating, and applying graph neural network models on chemical datasets.

Use cases

• predict molecular properties from SMILES strings
• train a graph neural network on chemical property data
• predict reaction properties with learned representations
• screen drug candidate molecules for desired properties
• run hyperparameter optimization for molecular property models
• interpret which atoms drive a property prediction

When to choose

• you need state-of-the-art MPNN models for molecular property prediction
• you want a maintained, well-documented tool with CLI and Python API for cheminformatics ML
• you are doing drug discovery or materials research requiring property prediction

When to avoid

• you need general-purpose graph neural networks beyond molecular graphs
• you want a no-code GUI tool rather than Python/CLI workflows
• your data is not chemical structures or reactions

Facets

library · maturity active

machine-learning deep-learning chemistry machine-learning healthcare python cli cross-platform graph-neural-networks message-passing-neural-networks molecular-property-prediction drug-discovery cheminformatics

Member repositories

For agents

markdown · JSON · MCP: product_card(name="chemprop/chemprop")