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An enumerative algorithm for de novo design of proteins with diverse pocket structures

To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a m...

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Autores principales: Basanta, Benjamin, Bick, Matthew J., Bera, Asim K., Norn, Christoffer, Chow, Cameron M., Carter, Lauren P., Goreshnik, Inna, Dimaio, Frank, Baker, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486743/
https://www.ncbi.nlm.nih.gov/pubmed/32839327
http://dx.doi.org/10.1073/pnas.2005412117
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author Basanta, Benjamin
Bick, Matthew J.
Bera, Asim K.
Norn, Christoffer
Chow, Cameron M.
Carter, Lauren P.
Goreshnik, Inna
Dimaio, Frank
Baker, David
author_facet Basanta, Benjamin
Bick, Matthew J.
Bera, Asim K.
Norn, Christoffer
Chow, Cameron M.
Carter, Lauren P.
Goreshnik, Inna
Dimaio, Frank
Baker, David
author_sort Basanta, Benjamin
collection PubMed
description To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed an enumerative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The enumerative algorithm was tested and refined through feedback from two rounds of large-scale experimental testing, involving in total the assembly of synthetic genes encoding 7,896 designs and assessment of their stability on yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small-molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins.
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spelling pubmed-74867432020-09-23 An enumerative algorithm for de novo design of proteins with diverse pocket structures Basanta, Benjamin Bick, Matthew J. Bera, Asim K. Norn, Christoffer Chow, Cameron M. Carter, Lauren P. Goreshnik, Inna Dimaio, Frank Baker, David Proc Natl Acad Sci U S A Biological Sciences To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed an enumerative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The enumerative algorithm was tested and refined through feedback from two rounds of large-scale experimental testing, involving in total the assembly of synthetic genes encoding 7,896 designs and assessment of their stability on yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small-molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins. National Academy of Sciences 2020-09-08 2020-08-24 /pmc/articles/PMC7486743/ /pubmed/32839327 http://dx.doi.org/10.1073/pnas.2005412117 Text en Copyright © 2020 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access 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
Basanta, Benjamin
Bick, Matthew J.
Bera, Asim K.
Norn, Christoffer
Chow, Cameron M.
Carter, Lauren P.
Goreshnik, Inna
Dimaio, Frank
Baker, David
An enumerative algorithm for de novo design of proteins with diverse pocket structures
title An enumerative algorithm for de novo design of proteins with diverse pocket structures
title_full An enumerative algorithm for de novo design of proteins with diverse pocket structures
title_fullStr An enumerative algorithm for de novo design of proteins with diverse pocket structures
title_full_unstemmed An enumerative algorithm for de novo design of proteins with diverse pocket structures
title_short An enumerative algorithm for de novo design of proteins with diverse pocket structures
title_sort enumerative algorithm for de novo design of proteins with diverse pocket structures
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486743/
https://www.ncbi.nlm.nih.gov/pubmed/32839327
http://dx.doi.org/10.1073/pnas.2005412117
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