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Rosetta:MSF: a modular framework for multi-state computational protein design
Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5484525/ https://www.ncbi.nlm.nih.gov/pubmed/28604768 http://dx.doi.org/10.1371/journal.pcbi.1005600 |
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author | Löffler, Patrick Schmitz, Samuel Hupfeld, Enrico Sterner, Reinhard Merkl, Rainer |
author_facet | Löffler, Patrick Schmitz, Samuel Hupfeld, Enrico Sterner, Reinhard Merkl, Rainer |
author_sort | Löffler, Patrick |
collection | PubMed |
description | Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)(8)-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design. |
format | Online Article Text |
id | pubmed-5484525 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54845252017-07-11 Rosetta:MSF: a modular framework for multi-state computational protein design Löffler, Patrick Schmitz, Samuel Hupfeld, Enrico Sterner, Reinhard Merkl, Rainer PLoS Comput Biol Research Article Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)(8)-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design. Public Library of Science 2017-06-12 /pmc/articles/PMC5484525/ /pubmed/28604768 http://dx.doi.org/10.1371/journal.pcbi.1005600 Text en © 2017 Löffler 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Löffler, Patrick Schmitz, Samuel Hupfeld, Enrico Sterner, Reinhard Merkl, Rainer Rosetta:MSF: a modular framework for multi-state computational protein design |
title | Rosetta:MSF: a modular framework for multi-state computational protein design |
title_full | Rosetta:MSF: a modular framework for multi-state computational protein design |
title_fullStr | Rosetta:MSF: a modular framework for multi-state computational protein design |
title_full_unstemmed | Rosetta:MSF: a modular framework for multi-state computational protein design |
title_short | Rosetta:MSF: a modular framework for multi-state computational protein design |
title_sort | rosetta:msf: a modular framework for multi-state computational protein design |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5484525/ https://www.ncbi.nlm.nih.gov/pubmed/28604768 http://dx.doi.org/10.1371/journal.pcbi.1005600 |
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