Accurate positioning of functional residues with robotics-inspired computational protein design

Author:

Krivacic Cody12,Kundert Kale23,Pan Xingjie12ORCID,Pache Roland A.2ORCID,Liu Lin2ORCID,O Conchúir Shane2,Jeliazkov Jeliazko R.4,Gray Jeffrey J.5ORCID,Thompson Michael C.2,Fraser James S.1236ORCID,Kortemme Tanja1236ORCID

Affiliation:

1. UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA 94158

2. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158

3. Biophysics Graduate Program, University of California, San Francisco, CA 94158

4. Program in Molecular Biophysics, Johns Hopkins University, Baltimore, MD 21218

5. Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218

6. Quantitative Biosciences Institute, University of California, San Francisco, CA 94158

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.

Funder

HHS | NIH | National Institute of General Medical Sciences

National Science Foundation

W. M. Keck Foundation

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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