Deriving a data-driven principle that has the power of explaining physical and chemical nature of biological systems, which we harness to accelerate drug discoveries.

To derive a data-driven principle that has the power of explaining physical and chemical nature of biological systems, which we harness to accelerate drug discoveries.

A data-driven atom-based scoring function is learned from 100,000 protein crystal structures containing information of >100 million amino acid side chains.
A dynamic deep neural network specifically designed for chemical informatics.

Beating current gold standard in computation-aided drug discovery:
Drug pocket side chain conformation prediction and drug docking with significantly increased accuracy compared to standard method.
Prediction of chemical compound characteristics (solubility, binding affinity, etc) significantly better than current standard.