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Ding D, Shaw AY, Sinai S, Rollins N, Prywes N, Savage DF, Laub MT, Marks DS. Protein design using structure-based residue preferences. Nat Commun 2024; 15:1639. [PMID: 38388493 PMCID: PMC10884402 DOI: 10.1038/s41467-024-45621-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 01/29/2024] [Indexed: 02/24/2024] Open
Abstract
Recent developments in protein design rely on large neural networks with up to 100s of millions of parameters, yet it is unclear which residue dependencies are critical for determining protein function. Here, we show that amino acid preferences at individual residues-without accounting for mutation interactions-explain much and sometimes virtually all of the combinatorial mutation effects across 8 datasets (R2 ~ 78-98%). Hence, few observations (~100 times the number of mutated residues) enable accurate prediction of held-out variant effects (Pearson r > 0.80). We hypothesized that the local structural contexts around a residue could be sufficient to predict mutation preferences, and develop an unsupervised approach termed CoVES (Combinatorial Variant Effects from Structure). Our results suggest that CoVES outperforms not just model-free methods but also similarly to complex models for creating functional and diverse protein variants. CoVES offers an effective alternative to complicated models for identifying functional protein mutations.
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Affiliation(s)
- David Ding
- Innovative Genomics Institute, University of California, Berkeley, CA, 94720, USA.
| | - Ada Y Shaw
- Department of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Sam Sinai
- Dyno Therapeutics, Watertown, MA, 02472, USA
| | - Nathan Rollins
- Seismic Therapeutics, Lab Central, Cambridge, MA, 02142, USA
| | - Noam Prywes
- Innovative Genomics Institute, University of California, Berkeley, CA, 94720, USA
| | - David F Savage
- Innovative Genomics Institute, University of California, Berkeley, CA, 94720, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA
- Howard Hughes Medical Institute, University of California, Berkeley, CA, 94720, USA
| | - Michael T Laub
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Debora S Marks
- Department of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA.
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