Accurate positioning of functional residues with robotics-inspired computational protein design
Category
Published on
Type
journal-article
Author
Cody Krivacic and Kale Kundert and Xingjie Pan and Roland A. Pache and Lin Liu and Shane O Conchúir and Jeliazko R. Jeliazkov and Jeffrey J. Gray and Michael C. Thompson and James S. Fraser and Tanja Kortemme
Citation
Krivacic, C., Kundert, K., Pan, X., Pache, R. A., Liu, L., O Conchúir, S., Jeliazkov, J. R., Gray, J. J., Thompson, M. C., Fraser, J. S., & Kortemme, T. (2022). Accurate positioning of functional residues with robotics-inspired computational protein design. Proceedings of the National Academy of Sciences, 119(11). https://doi.org/10.1073/pnas.2115480119
Abstract
Significance
Computational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geometries, which remains a major challenge. Here, we develop computational methods that design and predict local protein geometries with greater accuracy than existing methods. Then, as a proof of concept, we leverage these methods to design new protein conformations in the enzyme ketosteroid isomerase that change the protein’s preference for a key functional residue. Our computational methods are openly accessible and can be applied to the design of other intricate geometries customized for new user-defined protein functions.
