Zachary J Gale-Day

Feb 22, 2024 | dx.doi.org | Zachary J Gale-Day |Laura Shub |Kangway V. Chuang |Michael Keiser

Computational and machine learning (ML)-based approaches to predicting binding affinity are critical research directions in drug discovery. (1−4) A strong predictor of a ligand affinity is desirable both for hit identification in virtual screening and for computationally evaluating structure–activity relationships for hit expansion and hit-to-lead optimization.