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Generalized Fragment Picking in Rosetta: Design, Protocols and Applications

The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extracted from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends...

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Detalles Bibliográficos
Autores principales: Gront, Dominik, Kulp, Daniel W., Vernon, Robert M., Strauss, Charlie E. M., Baker, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3160850/
https://www.ncbi.nlm.nih.gov/pubmed/21887241
http://dx.doi.org/10.1371/journal.pone.0023294
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author Gront, Dominik
Kulp, Daniel W.
Vernon, Robert M.
Strauss, Charlie E. M.
Baker, David
author_facet Gront, Dominik
Kulp, Daniel W.
Vernon, Robert M.
Strauss, Charlie E. M.
Baker, David
author_sort Gront, Dominik
collection PubMed
description The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extracted from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends the functionality of the previous program (nnmake) and opens the door for new approaches to structure modeling. We provide a detailed description of the code design and architecture, highlighting its modularity, and new features such as extensibility, total control over the fragment picking workflow and scoring system customization. We demonstrate that the program provides at least as good building blocks for ab-initio structure prediction as the previous program, and provide examples of the wide range of applications that are now accessible.
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spelling pubmed-31608502011-09-01 Generalized Fragment Picking in Rosetta: Design, Protocols and Applications Gront, Dominik Kulp, Daniel W. Vernon, Robert M. Strauss, Charlie E. M. Baker, David PLoS One Research Article The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extracted from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends the functionality of the previous program (nnmake) and opens the door for new approaches to structure modeling. We provide a detailed description of the code design and architecture, highlighting its modularity, and new features such as extensibility, total control over the fragment picking workflow and scoring system customization. We demonstrate that the program provides at least as good building blocks for ab-initio structure prediction as the previous program, and provide examples of the wide range of applications that are now accessible. Public Library of Science 2011-08-24 /pmc/articles/PMC3160850/ /pubmed/21887241 http://dx.doi.org/10.1371/journal.pone.0023294 Text en Gront 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
Gront, Dominik
Kulp, Daniel W.
Vernon, Robert M.
Strauss, Charlie E. M.
Baker, David
Generalized Fragment Picking in Rosetta: Design, Protocols and Applications
title Generalized Fragment Picking in Rosetta: Design, Protocols and Applications
title_full Generalized Fragment Picking in Rosetta: Design, Protocols and Applications
title_fullStr Generalized Fragment Picking in Rosetta: Design, Protocols and Applications
title_full_unstemmed Generalized Fragment Picking in Rosetta: Design, Protocols and Applications
title_short Generalized Fragment Picking in Rosetta: Design, Protocols and Applications
title_sort generalized fragment picking in rosetta: design, protocols and applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3160850/
https://www.ncbi.nlm.nih.gov/pubmed/21887241
http://dx.doi.org/10.1371/journal.pone.0023294
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