Chemprop is a message passing neural network for molecular property prediction.

At its core, Chemprop contains a directed message passing neural network (D-MPNN), which was first presented in Analyzing Learned Molecular Representations for Property Prediction. The Chemprop D-MPNN shows strong molecular property prediction capabilities across a range of properties, from quantum mechanical energy to human toxicity.

Chemprop was later used in the paper A Deep Learning Approach to Antibiotic Discovery to discover promising new antibiotics by predicting the likelihood that a molecule would inhibit the growth of E. coli.

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