Mega-scale experimental analysis of protein folding stability in biology and protein design
Abstract Advances in DNA sequencing and machine learning are illuminating protein sequences and structures on an enormous scale. However, the energetics driving folding are invisible in these structures and remain largely unknown. The hidden thermodynamics of folding can drive disease, shape protein evolution, and guide protein engineering, and new approaches are needed to reveal these thermodynamics for every sequence and structure. We present cDNA display proteolysis, a new 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 ~850,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 354 natural and 188 de novo designed protein domains 40-72 amino acids in length. Using this immense 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.One-Sentence Summary Massively parallel measurement of protein folding stability by cDNA display proteolysis.
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 23. Apr. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Tsuboyama, Kotaro [VerfasserIn] |
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| doi: |
10.1101/2022.12.06.519132 |
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| PPN (Katalog-ID): |
XBI038107821 |
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| 520 | |a Abstract Advances in DNA sequencing and machine learning are illuminating protein sequences and structures on an enormous scale. However, the energetics driving folding are invisible in these structures and remain largely unknown. The hidden thermodynamics of folding can drive disease, shape protein evolution, and guide protein engineering, and new approaches are needed to reveal these thermodynamics for every sequence and structure. We present cDNA display proteolysis, a new 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 ~850,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 354 natural and 188 de novo designed protein domains 40-72 amino acids in length. Using this immense 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.One-Sentence Summary Massively parallel measurement of protein folding stability by cDNA display proteolysis | ||
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| 700 | 1 | |a Chen, Jonathan |e verfasserin |4 aut | |
| 700 | 1 | |a Laine, Elodie |e verfasserin |0 (orcid)0000-0003-4870-6304 |4 aut | |
| 700 | 1 | |a Mohseni Behbahani, Yasser |e verfasserin |0 (orcid)0000-0003-0254-6595 |4 aut | |
| 700 | 1 | |a Weinstein, Jonathan J. |e verfasserin |4 aut | |
| 700 | 1 | |a Mangan, Niall M. |e verfasserin |0 (orcid)0000-0002-3491-8341 |4 aut | |
| 700 | 1 | |a Ovchinnikov, Sergey |e verfasserin |0 (orcid)0000-0003-2774-2744 |4 aut | |
| 700 | 1 | |a Rocklin, Gabriel J. |e verfasserin |0 (orcid)0000-0003-2253-5631 |4 aut | |
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