Proteochemometrics – recent developments in bioactivity and selectivity modeling

Proteochemometrics is a machine learning based modeling approach relying on a combination of ligand and protein descriptors. With ongoing developments in machine learning and increases in public data the technique is more frequently applied in early drug discovery, typically in ligand–target binding prediction. Common applications include improvements to single target quantitative structure-activity relationship models, protein selectivity and...