Patricia Babbitt earned her Ph.D. in Medicinal Chemistry from the University of California, San Francisco (UCSF). She is currently Professor of Computational Biology in the Department of Bioengineering and Therapeutic Sciences, the Department of Pharmaceutical Chemistry, and the California Institute for Quantitative Biosciences (QB3). She is the Director of the UCSF Biological and Medical Informatics Graduate Program and serves on Advisory Boards for the UniProt Database, the Metacyc Metabolic Pathway Database, the HHMI Scientific Review Board, and as a Deputy Editor for PLoS Computational Biology.
Her research focuses on protein structure-function relationships in enzyme superfamilies, aiming to understand the "architectural principles" underlying how some protein scaffolds have evolved to enable many different functions. To take advantage of the huge volumes of sequencing data now available, her group uses graphical network models to summarize on a global scale structure-function relationships in very large and functionally diverse superfamilies. The results show that only a small proportion of these enzymes have been functionally or structurally characterized and suggest that many chemical capabilities remain undiscovered across the biosphere. This observation is important for functional inference, identification of misannotated proteins, and for providing guidance for selection of targets for experimental and structural investigation.