Combining co-evolution and secondary structure prediction to improve fragment library generation

<strong>Motivation</strong> Recent advances in co-evolution techniques have made possible the accurate prediction of protein structures in the absence of a template. Here, we provide a general approach that further utilizes co-evolution constraints to generate better fragment libraries f...

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Үндсэн зохиолчид: de Oliveira, S, Deane, C
Формат: Journal article
Хэл сонгох:English
Хэвлэсэн: Oxford University Press 2018
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author de Oliveira, S
Deane, C
author_facet de Oliveira, S
Deane, C
author_sort de Oliveira, S
collection OXFORD
description <strong>Motivation</strong> Recent advances in co-evolution techniques have made possible the accurate prediction of protein structures in the absence of a template. Here, we provide a general approach that further utilizes co-evolution constraints to generate better fragment libraries for fragment-based protein structure prediction. <strong>Results</strong> We have compared five different fragment library generation programmes on three different datasets encompassing over 400 unique protein folds. We show that considering the secondary structure of the fragments when assembling these libraries provides a critical way to assess their usefulness to structure prediction. We then use co-evolution constraints to improve the fragment libraries by enriching them with fragments that satisfy constraints and discarding those that do not. These improved libraries have better precision and lead to consistently better modelling results. <strong>Availability and implementation</strong> Data is available for download from: http://opig.stats.ox.ac.uk/resources. Flib-Coevo is available for download from: https://github.com/sauloho/Flib-Coevo.
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spelling oxford-uuid:ca3b892e-17aa-4e6c-88c2-5e9075b2a94c2022-03-27T07:05:52ZCombining co-evolution and secondary structure prediction to improve fragment library generationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ca3b892e-17aa-4e6c-88c2-5e9075b2a94cEnglishSymplectic Elements at OxfordOxford University Press2018de Oliveira, SDeane, C<strong>Motivation</strong> Recent advances in co-evolution techniques have made possible the accurate prediction of protein structures in the absence of a template. Here, we provide a general approach that further utilizes co-evolution constraints to generate better fragment libraries for fragment-based protein structure prediction. <strong>Results</strong> We have compared five different fragment library generation programmes on three different datasets encompassing over 400 unique protein folds. We show that considering the secondary structure of the fragments when assembling these libraries provides a critical way to assess their usefulness to structure prediction. We then use co-evolution constraints to improve the fragment libraries by enriching them with fragments that satisfy constraints and discarding those that do not. These improved libraries have better precision and lead to consistently better modelling results. <strong>Availability and implementation</strong> Data is available for download from: http://opig.stats.ox.ac.uk/resources. Flib-Coevo is available for download from: https://github.com/sauloho/Flib-Coevo.
spellingShingle de Oliveira, S
Deane, C
Combining co-evolution and secondary structure prediction to improve fragment library generation
title Combining co-evolution and secondary structure prediction to improve fragment library generation
title_full Combining co-evolution and secondary structure prediction to improve fragment library generation
title_fullStr Combining co-evolution and secondary structure prediction to improve fragment library generation
title_full_unstemmed Combining co-evolution and secondary structure prediction to improve fragment library generation
title_short Combining co-evolution and secondary structure prediction to improve fragment library generation
title_sort combining co evolution and secondary structure prediction to improve fragment library generation
work_keys_str_mv AT deoliveiras combiningcoevolutionandsecondarystructurepredictiontoimprovefragmentlibrarygeneration
AT deanec combiningcoevolutionandsecondarystructurepredictiontoimprovefragmentlibrarygeneration