Our lab's long-term goal is to enable reliable and completely computational design of efficient, selective, and stable protein binders and enzymes. To achieve this goal, we are developing a unique strategy called evolution-guided atomistic design that uses information encoded in the evolutionary history of protein families to infer what structure and sequence features are likely to be tolerated in any given protein. We then use these rules to guide Rosetta atomistic design calculations in the search for new proteins with desired functions. To test our algorithms, we design new proteins that don't exist in nature and carry out wet-lab experiments either in-house or with our collaborators. Feedback from these experiments then enables the development of more sophisticated design algorithms. We therefore combine cutting-edge computational methods development with high-throughput experimental screening and stringent biochemical and structural analysis of designed proteins.
- Khersonsky, O.; Fleishman, S. J. Why Reinvent the Wheel? Building New Proteins Based on Ready-Made Parts. Protein Sci. 2016, 25 (7), 1179–1187.
- Goldenzweig, A.; Fleishman, S. J. Principles of Protein Stability and Their Application in Computational Design. Annu. Rev. Biochem. 2018, 87, 105–129.