How do we do it?
The technology behind PharmAI’s DiscoveryEngine allows for an unprecedented level of detail to represent drug-target complexes. Besides geometric comparison of binding sites based on local alignments, non-covalent interactions were shown to improve the prediction of binding site similarity significantly. Over many years, PharmAI refined and improved this technology and applied it to reposition known drugs to new targets for cancer or malaria. At its core, pharmAI’s technology leverages 3D structure of drug-target complex, calculates similarities to produce predictions, and ranks them using artificial intelligence.
Interactions Unique as Your Fingerprint
pharmAI's DiscoveryEngine translates protein-ligand complexes into unique fingerprints. This allows for the fast computation of similarities across arbitrary chemical libraries for new compound prediction. We can use the fingerprint even for the prediction of potential off-targets.
Analyze Binding Sites
The key to pharmAI's disrupting technology is the exploitation of geometric binding site properties and non-covalent interaction patterns. The unique combination of these two approaches allows us to generalize ligand binding and predict new scaffolds.
Our Steps to New Scaffolds and Off-Targets
Binding Site Analysis
Hit rate 500x higher than HTS rates, 8x-3x improvement over than state-of-the-art methods.
Comparison to Industry Leaders
Our hit rate outperforms industry leaders: