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Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction

Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, t...

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Autores principales: Braun, Tatjana, Koehler Leman, Julia, Lange, Oliver F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4694711/
https://www.ncbi.nlm.nih.gov/pubmed/26713437
http://dx.doi.org/10.1371/journal.pcbi.1004661
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author Braun, Tatjana
Koehler Leman, Julia
Lange, Oliver F.
author_facet Braun, Tatjana
Koehler Leman, Julia
Lange, Oliver F.
author_sort Braun, Tatjana
collection PubMed
description Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.
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spelling pubmed-46947112016-01-13 Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction Braun, Tatjana Koehler Leman, Julia Lange, Oliver F. PLoS Comput Biol Research Article Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs. Public Library of Science 2015-12-29 /pmc/articles/PMC4694711/ /pubmed/26713437 http://dx.doi.org/10.1371/journal.pcbi.1004661 Text en © 2015 Braun 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
Braun, Tatjana
Koehler Leman, Julia
Lange, Oliver F.
Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction
title Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction
title_full Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction
title_fullStr Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction
title_full_unstemmed Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction
title_short Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction
title_sort combining evolutionary information and an iterative sampling strategy for accurate protein structure prediction
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4694711/
https://www.ncbi.nlm.nih.gov/pubmed/26713437
http://dx.doi.org/10.1371/journal.pcbi.1004661
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