Function, evolution and engineering of proteins

The sequence-function landscape of a protein is the connection of genotype and phenotype at a molecular level. Although abstract, this concept has many real-world applications. Mapping and predicting this space would improve our basic science understanding of macromolecular function in the cell, clarify the role of genetic variation in causing disease, and lead to our ability to design biological therapeutics with improved potency and specificity. The goal of our work is to develop experimental methods to systematically explore the mutational landscape of biomedically relevant proteins such as CRISPR-Cas genome editing enzymes. A related aspect of our work is to create new types of assays that yield robust measurements of real biochemical parameters, rather than relative measurements which are typically measured out of convenience. In the long term, our goal is to couple this data, mechanistic studies, and machine learning tools to develop state of the art methods for predicting and engineering protein function. Project Number: 1R35GM158173-01 | Fiscal Year: 2025 | NIH Institute/Center: National Institute of General Medical Sciences (NIGMS) | Principal Investigator: David Savage | Institution: UNIVERSITY OF CALIFORNIA BERKELEY, BERKELEY, CA | Award Amount: $361,952 | Activity Code: R35 | Study Section: Maximizing Investigators' Research Award - E Study Section[MRAE] View on NIH RePORTER: https://reporter.nih.gov/project-details/11090836