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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 limi...
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Published in: | PLoS computational biology 2015-11, Vol.11 (11), p.e1004556 |
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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 (ΔTm = 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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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 (ΔTm = 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.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1004556</identifier><identifier>PMID: 26529612</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Biocatalysts ; Computational Biology - methods ; Computer Simulation ; Databases, Genetic ; Enzyme Stability - genetics ; Enzymes ; Experiments ; Gene expression ; Gene mutations ; Lyases - chemistry ; Lyases - genetics ; Lyases - metabolism ; Models, Molecular ; Mutagenesis ; Mutation ; Nanomaterials ; Point Mutation - genetics ; Point Mutation - physiology ; Protein Engineering - methods ; Proteins ; State budgets ; Studies ; Temperature</subject><ispartof>PLoS computational biology, 2015-11, Vol.11 (11), p.e1004556</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Bednar et al 2015 Bednar et al</rights><rights>2015 Public Library of Science. 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 credited: Bednar D, Beerens K, Sebestova E, Bendl J, Khare S, Chaloupkova R, et al. (2015) FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants. 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We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 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.</description><subject>Analysis</subject><subject>Biocatalysts</subject><subject>Computational Biology - methods</subject><subject>Computer Simulation</subject><subject>Databases, Genetic</subject><subject>Enzyme Stability - genetics</subject><subject>Enzymes</subject><subject>Experiments</subject><subject>Gene expression</subject><subject>Gene mutations</subject><subject>Lyases - chemistry</subject><subject>Lyases - genetics</subject><subject>Lyases - metabolism</subject><subject>Models, Molecular</subject><subject>Mutagenesis</subject><subject>Mutation</subject><subject>Nanomaterials</subject><subject>Point Mutation - genetics</subject><subject>Point Mutation - physiology</subject><subject>Protein Engineering - methods</subject><subject>Proteins</subject><subject>State budgets</subject><subject>Studies</subject><subject>Temperature</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNqVUtFuFCEUnRiNrdU_MDqvPswKw8AMPpjUdaubVG20PpM7A0zZsDABprF_L-tum-6j4YHL5Zxzw-EUxWuMFpi0-P3Gz8GBXUxDbxYYoYZS9qQ4xZSSqiW0e_qoPilexLhBKJecPS9OakZrznB9WsCFCeoq-PShXDkVxruqBCfL1a23czLeVZ8gKlku_XaaE-w6YMvPKprRlV6X1zcqbH1M0FtVfpttMpNV1ZU3LuVjApfiy-KZBhvVq8N-Vvy-WF0vv1aXP76sl-eX1cBanCrMCeqGpmkYYAqSklzqnsuOy3bgLauZRMA1lUxxDbjTmrRSUkkwcNTRgZwVb_e6k_VRHNyJArcNZw0lNcuI9R4hPWzEFMwWwp3wYMS_hg-jgJDMYJUgknQYYYwJy8Yy1AOXEiFOa0U4YJW1Ph6mzf1WyUG5FMAeiR7fOHMjRn8rGkZw_qossNgLjJDnGad9hg15SbU1g3dKm9w_b0iLKK9xlwnvjggZk9SfNMIco1j_-vkf2O_H2GaPHYKPMSj98AiMxC5p916KXdLEIWmZ9uaxAQ-k-2iRvzJ_0Fs</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Bednar, David</creator><creator>Beerens, Koen</creator><creator>Sebestova, Eva</creator><creator>Bendl, Jaroslav</creator><creator>Khare, Sagar</creator><creator>Chaloupkova, Radka</creator><creator>Prokop, Zbynek</creator><creator>Brezovsky, Jan</creator><creator>Baker, David</creator><creator>Damborsky, Jiri</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20151101</creationdate><title>FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants</title><author>Bednar, David ; Beerens, Koen ; Sebestova, Eva ; Bendl, Jaroslav ; Khare, Sagar ; Chaloupkova, Radka ; Prokop, Zbynek ; Brezovsky, Jan ; Baker, David ; Damborsky, Jiri</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c671t-19308c4446a15ad53444fb9d89d7c97626d0a9f5d6e9fa18ff37dd5d31a9085c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Analysis</topic><topic>Biocatalysts</topic><topic>Computational Biology - methods</topic><topic>Computer Simulation</topic><topic>Databases, Genetic</topic><topic>Enzyme Stability - genetics</topic><topic>Enzymes</topic><topic>Experiments</topic><topic>Gene expression</topic><topic>Gene mutations</topic><topic>Lyases - chemistry</topic><topic>Lyases - genetics</topic><topic>Lyases - metabolism</topic><topic>Models, Molecular</topic><topic>Mutagenesis</topic><topic>Mutation</topic><topic>Nanomaterials</topic><topic>Point Mutation - genetics</topic><topic>Point Mutation - physiology</topic><topic>Protein Engineering - methods</topic><topic>Proteins</topic><topic>State budgets</topic><topic>Studies</topic><topic>Temperature</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bednar, David</creatorcontrib><creatorcontrib>Beerens, Koen</creatorcontrib><creatorcontrib>Sebestova, Eva</creatorcontrib><creatorcontrib>Bendl, Jaroslav</creatorcontrib><creatorcontrib>Khare, Sagar</creatorcontrib><creatorcontrib>Chaloupkova, Radka</creatorcontrib><creatorcontrib>Prokop, Zbynek</creatorcontrib><creatorcontrib>Brezovsky, Jan</creatorcontrib><creatorcontrib>Baker, David</creatorcontrib><creatorcontrib>Damborsky, Jiri</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale in Context: Science</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bednar, David</au><au>Beerens, Koen</au><au>Sebestova, Eva</au><au>Bendl, Jaroslav</au><au>Khare, Sagar</au><au>Chaloupkova, Radka</au><au>Prokop, Zbynek</au><au>Brezovsky, Jan</au><au>Baker, David</au><au>Damborsky, Jiri</au><au>Dokholyan, Nikolay V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>11</volume><issue>11</issue><spage>e1004556</spage><pages>e1004556-</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>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 (ΔTm = 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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26529612</pmid><doi>10.1371/journal.pcbi.1004556</doi><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Biocatalysts Computational Biology - methods Computer Simulation Databases, Genetic Enzyme Stability - genetics Enzymes Experiments Gene expression Gene mutations Lyases - chemistry Lyases - genetics Lyases - metabolism Models, Molecular Mutagenesis Mutation Nanomaterials Point Mutation - genetics Point Mutation - physiology Protein Engineering - methods Proteins State budgets Studies Temperature |
title | FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants |
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