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

Kotaro Tsuboyama, Justas Dauparas, Jonathan Chen, Elodie Laine, Yasser Mohseni Behbahani, Jonathan J. Weinstein, Niall M. Mangan, Sergey Ovchinnikov and Gabriel J. Rocklin ()
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Kotaro Tsuboyama: Northwestern University Feinberg School of Medicine
Justas Dauparas: University of Washington
Jonathan Chen: Northwestern University Feinberg School of Medicine
Elodie Laine: Sorbonne Université, CNRS, IBPS, Laboratory of Computational and Quantitative Biology (LCQB), UMR 7238
Yasser Mohseni Behbahani: Sorbonne Université, CNRS, IBPS, Laboratory of Computational and Quantitative Biology (LCQB), UMR 7238
Jonathan J. Weinstein: Weizmann Institute of Science
Niall M. Mangan: Northwestern University
Sergey Ovchinnikov: Harvard University
Gabriel J. Rocklin: Northwestern University Feinberg School of Medicine

Nature, 2023, vol. 620, issue 7973, 434-444

Abstract: Abstract Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale1. However, the energetics driving folding are invisible in these structures and remain largely unknown2. The hidden thermodynamics of folding can drive disease3,4, shape protein evolution5–7 and guide protein engineering8–10, 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.

Date: 2023
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DOI: 10.1038/s41586-023-06328-6

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