Mega-scale experimental analysis of protein folding stability in biology and design.

Autor: Tsuboyama K; Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.; Center for Synthetic Biology, Northwestern University, Evanston, IL, USA.; PRESTO, Japan Science and Technology Agency, Tokyo, Japan.; Institute of Industrial Science, The University of Tokyo, Tokyo, Japan., Dauparas J; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Chen J; Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.; Center for Synthetic Biology, Northwestern University, Evanston, IL, USA.; McCormick School of Engineering, Northwestern University, Evanston, IL, USA., Laine E; Sorbonne Université, CNRS, IBPS, Laboratory of Computational and Quantitative Biology (LCQB), UMR 7238, Paris, France., Mohseni Behbahani Y; Sorbonne Université, CNRS, IBPS, Laboratory of Computational and Quantitative Biology (LCQB), UMR 7238, Paris, France., Weinstein JJ; Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel., Mangan NM; Center for Synthetic Biology, Northwestern University, Evanston, IL, USA.; Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA., Ovchinnikov S; John Harvard Distinguished Science Fellowship Program, Harvard University, Cambridge, MA, USA., Rocklin GJ; Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. grocklin@gmail.com.; Center for Synthetic Biology, Northwestern University, Evanston, IL, USA. grocklin@gmail.com.
Jazyk: angličtina
Zdroj: Nature [Nature] 2023 Aug; Vol. 620 (7973), pp. 434-444. Date of Electronic Publication: 2023 Jul 19.
DOI: 10.1038/s41586-023-06328-6
Abstrakt: Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale 1 . However, the energetics driving folding are invisible in these structures and remain largely unknown 2 . The hidden thermodynamics of folding can drive disease 3,4 , shape protein evolution 5-7 and guide protein engineering 8-10 , and new approaches are needed to reveal these thermodynamics for every sequence and structure. Here we present cDNA display proteolysis, a method for measuring thermodynamic folding stability for up to 900,000 protein domains in a one-week experiment. From 1.8 million measurements in total, we curated a set of around 776,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 331 natural and 148 de novo designed protein domains 40-72 amino acids in length. Using this extensive dataset, we quantified (1) environmental factors influencing amino acid fitness, (2) thermodynamic couplings (including unexpected interactions) between protein sites, and (3) the global divergence between evolutionary amino acid usage and protein folding stability. We also examined how our approach could identify stability determinants in designed proteins and evaluate design methods. The cDNA display proteolysis method is fast, accurate and uniquely scalable, and promises to reveal the quantitative rules for how amino acid sequences encode folding stability.
(© 2023. The Author(s).)
Databáze: MEDLINE
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