Automated protein optimisation

Proteins in nature are subject to evolutionary processes that optimise their activities. In recent decades, scientists have emulated natural evolutionary process in the lab, enabling the optimisation of proteins for human needs, thus generating efficient enzymes and binders. But evolution is an iterative process in which every change in a protein (mutation) must result in one that is at least as functional as its predecessor or the variant would be purged by the powerful forces of selection. Thus, lab evolution experiments may take years of tedious trial-and-error. We developed several methods that enable rapid, one-shot optimisation of protein activities, generating enzymes that degrade a broad spectrum of highly toxic nerve agents, antibodies with much improved affinity and stability, and even a much cheaper and more stable variant of a protein that is the prime candidate to serve as a vaccine for malaria. One of the most important goals for the lab is to enable broad use of our algorithms by biochemists and protein engineers, and we therefore develop web servers that allow researchers around the world to customise our design protocols for their particular needs. The web servers carry out the calculations on our lab's computer cluster and return models of improved binders and enzymes by email. You're most welcome to try these web servers yourself!

Further reading

  • Goldenzweig, A.; Goldsmith, M.; Hill, S. E.; Gertman, O.; Laurino, P.; Ashani, Y.; Dym, O.; Unger, T.; Albeck, S.; Prilusky, J.; Lieberman, R. L.; Aharoni, A.; Silman, I.; Sussman, J. L.; Tawfik, D. S.; Fleishman, S. J. Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability. Mol. Cell 2016, 63 (2), 337–346.
  • Campeotto, I.; Goldenzweig, A.; Davey, J.; Barfod, L.; Marshall, J. M.; Silk, S. E.; Wright, K. E.; Draper, S. J.; Higgins, M. K.; Fleishman, S. J. One-Step Design of a Stable Variant of the Malaria Invasion Protein RH5 for Use as a Vaccine Immunogen. Proc. Natl. Acad. Sci. U. S. A. 2017, 114 (5), 998–1002.
  • Khersonsky, O.; Lipsh, R.; Avizemer, Z.; Ashani, Y.; Goldsmith, M.; Leader, H.; Dym, O.; Rogotner, S.; Trudeau, D. L.; Prilusky, J.; Amengual-Rigo, P.; Guallar, V.; Tawfik, D. S.; Fleishman, S. J. Automated Design of Efficient and Functionally Diverse Enzyme Repertoires. Mol. Cell 2018, 72 (1), 178–186.e5.
  • Goldenzweig, A.; Fleishman, S. J. Principles of Protein Stability and Their Application in Computational Design. Annu. Rev. Biochem. 2018, 87, 105–129.