Brian K. Shoichet

Papers

Total Citations

234

H-Index

About

Brian K. Shoichet is a pioneering figure in computational drug discovery, whose work has fundamentally reshaped how new therapeutics are identified. His primary research areas span molecular recognition, protein-ligand docking, and the development of large-scale virtual screening methods. Shoichet is best known for demonstrating that computational screening can rival experimental high-throughput approaches, dramatically reducing costs and accelerating the discovery of lead compounds. His seminal 2005 review, "Virtual Screening in Drug Discovery," has garnered over 234 citations and remains a foundational text in the field. Beyond methodology, Shoichet has made transformative contributions by uncovering unexpected off-target interactions, including the discovery that many drugs act through polypharmacology—binding to multiple proteins. His lab has developed widely used docking algorithms and open-source tools that enable researchers worldwide to screen millions of compounds in silico. A member of the National Academy of Sciences, Shoichet’s work has led to the identification of novel ligands for G protein-coupled receptors and enzymes, with several compounds advancing to preclinical studies. His research continues to bridge computation and experimental biology, making him a leading voice in modern drug design.