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FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants

There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited r...

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Autores principales: Bednar, David, Beerens, Koen, Sebestova, Eva, Bendl, Jaroslav, Khare, Sagar, Chaloupkova, Radka, Prokop, Zbynek, Brezovsky, Jan, Baker, David, Damborsky, Jiri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4631455/
https://www.ncbi.nlm.nih.gov/pubmed/26529612
http://dx.doi.org/10.1371/journal.pcbi.1004556
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author Bednar, David
Beerens, Koen
Sebestova, Eva
Bendl, Jaroslav
Khare, Sagar
Chaloupkova, Radka
Prokop, Zbynek
Brezovsky, Jan
Baker, David
Damborsky, Jiri
author_facet Bednar, David
Beerens, Koen
Sebestova, Eva
Bendl, Jaroslav
Khare, Sagar
Chaloupkova, Radka
Prokop, Zbynek
Brezovsky, Jan
Baker, David
Damborsky, Jiri
author_sort Bednar, David
collection PubMed
description There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt’s reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔT (m) = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.
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spelling pubmed-46314552015-11-13 FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants Bednar, David Beerens, Koen Sebestova, Eva Bendl, Jaroslav Khare, Sagar Chaloupkova, Radka Prokop, Zbynek Brezovsky, Jan Baker, David Damborsky, Jiri PLoS Comput Biol Research Article There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt’s reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔT (m) = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications. Public Library of Science 2015-11-03 /pmc/articles/PMC4631455/ /pubmed/26529612 http://dx.doi.org/10.1371/journal.pcbi.1004556 Text en © 2015 Bednar et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Bednar, David
Beerens, Koen
Sebestova, Eva
Bendl, Jaroslav
Khare, Sagar
Chaloupkova, Radka
Prokop, Zbynek
Brezovsky, Jan
Baker, David
Damborsky, Jiri
FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants
title FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants
title_full FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants
title_fullStr FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants
title_full_unstemmed FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants
title_short FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants
title_sort fireprot: energy- and evolution-based computational design of thermostable multiple-point mutants
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4631455/
https://www.ncbi.nlm.nih.gov/pubmed/26529612
http://dx.doi.org/10.1371/journal.pcbi.1004556
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