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Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation

Designing entirely new protein structures remains challenging because we do not fully understand the biophysical determinants of folding stability. Yet, some protein folds are easier to design than others. Previous work identified the 43-residue ɑββɑ fold as especially challenging: The best designs...

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Autores principales: Kim, Tae-Eun, Tsuboyama, Kotaro, Houliston, Scott, Martell, Cydney M., Phoumyvong, Claire M., Lemak, Alexander, Haddox, Hugh K., Arrowsmith, Cheryl H., Rocklin, Gabriel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9564214/
https://www.ncbi.nlm.nih.gov/pubmed/36191185
http://dx.doi.org/10.1073/pnas.2122676119
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author Kim, Tae-Eun
Tsuboyama, Kotaro
Houliston, Scott
Martell, Cydney M.
Phoumyvong, Claire M.
Lemak, Alexander
Haddox, Hugh K.
Arrowsmith, Cheryl H.
Rocklin, Gabriel J.
author_facet Kim, Tae-Eun
Tsuboyama, Kotaro
Houliston, Scott
Martell, Cydney M.
Phoumyvong, Claire M.
Lemak, Alexander
Haddox, Hugh K.
Arrowsmith, Cheryl H.
Rocklin, Gabriel J.
author_sort Kim, Tae-Eun
collection PubMed
description Designing entirely new protein structures remains challenging because we do not fully understand the biophysical determinants of folding stability. Yet, some protein folds are easier to design than others. Previous work identified the 43-residue ɑββɑ fold as especially challenging: The best designs had only a 2% success rate, compared to 39 to 87% success for other simple folds [G. J. Rocklin et al., Science 357, 168–175 (2017)]. This suggested the ɑββɑ fold would be a useful model system for gaining a deeper understanding of folding stability determinants and for testing new protein design methods. Here, we designed over 10,000 new ɑββɑ proteins and found over 3,000 of them to fold into stable structures using a high-throughput protease-based assay. NMR, hydrogen-deuterium exchange, circular dichroism, deep mutational scanning, and scrambled sequence control experiments indicated that our stable designs fold into their designed ɑββɑ structures with exceptional stability for their small size. Our large dataset enabled us to quantify the influence of universal stability determinants including nonpolar burial, helix capping, and buried unsatisfied polar atoms, as well as stability determinants unique to the ɑββɑ topology. Our work demonstrates how large-scale design and test cycles can solve challenging design problems while illuminating the biophysical determinants of folding.
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spelling pubmed-95642142023-04-03 Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation Kim, Tae-Eun Tsuboyama, Kotaro Houliston, Scott Martell, Cydney M. Phoumyvong, Claire M. Lemak, Alexander Haddox, Hugh K. Arrowsmith, Cheryl H. Rocklin, Gabriel J. Proc Natl Acad Sci U S A Biological Sciences Designing entirely new protein structures remains challenging because we do not fully understand the biophysical determinants of folding stability. Yet, some protein folds are easier to design than others. Previous work identified the 43-residue ɑββɑ fold as especially challenging: The best designs had only a 2% success rate, compared to 39 to 87% success for other simple folds [G. J. Rocklin et al., Science 357, 168–175 (2017)]. This suggested the ɑββɑ fold would be a useful model system for gaining a deeper understanding of folding stability determinants and for testing new protein design methods. Here, we designed over 10,000 new ɑββɑ proteins and found over 3,000 of them to fold into stable structures using a high-throughput protease-based assay. NMR, hydrogen-deuterium exchange, circular dichroism, deep mutational scanning, and scrambled sequence control experiments indicated that our stable designs fold into their designed ɑββɑ structures with exceptional stability for their small size. Our large dataset enabled us to quantify the influence of universal stability determinants including nonpolar burial, helix capping, and buried unsatisfied polar atoms, as well as stability determinants unique to the ɑββɑ topology. Our work demonstrates how large-scale design and test cycles can solve challenging design problems while illuminating the biophysical determinants of folding. National Academy of Sciences 2022-10-03 2022-10-11 /pmc/articles/PMC9564214/ /pubmed/36191185 http://dx.doi.org/10.1073/pnas.2122676119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Kim, Tae-Eun
Tsuboyama, Kotaro
Houliston, Scott
Martell, Cydney M.
Phoumyvong, Claire M.
Lemak, Alexander
Haddox, Hugh K.
Arrowsmith, Cheryl H.
Rocklin, Gabriel J.
Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
title Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
title_full Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
title_fullStr Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
title_full_unstemmed Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
title_short Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
title_sort dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9564214/
https://www.ncbi.nlm.nih.gov/pubmed/36191185
http://dx.doi.org/10.1073/pnas.2122676119
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