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.
- Web Interface
- Training and Predicting
- Hyperparameter Optimization
- Command Line Arguments
- Neural Network Utility Functions
- Utility Functions
- Scikit-Learn Models
- Useful Scripts