Gerald J. Wyckoff
University of Missouri Kansas City
Modern drug discovery using in silico techniques is about sifting through large amounts of data to find signal in a sea of noise, and developing methodologies that do this efficiently. As a molecular evolutionary geneticist, I was used to finding faint signatures of positive selection in a sea of genomic noise. This led me to become involved with large scale genomic, and later proteomic, projects. This has allowed me to extend my knowledge in drug discovery towards chemical information signatures for high-throughput screening of compounds.
Focusing on how evolutionary knowledge can factor into drug discovery, Dr. Wyckoff has been creating and deploying new algorithms for better handling the targets of new chemical entities. The disconnect between proteins involved with disease and those generally targeted by commercially successful drugs is worrisome as drug target selection usually follows disease mapping initiatives. A focus in his career has been translating knowledge into the classroom, especially focusing on non-science majors to get them interested in careers in life and health sciences. His lab deals with aspects of Bioinformatics drug development and study of evolutionary processes at the molecular level.