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Incorporation of Local Structural Preference Potential Improves Fold Recognition

Fold recognition, or threading, is a popular protein structure modeling approach that uses known structure templates to build structures for those of unknown. The key to the success of fold recognition methods lies in the proper integration of sequence, physiochemical and structural information. Her...

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Detalles Bibliográficos
Autores principales: Hu, Yun, Dong, Xiaoxi, Wu, Aiping, Cao, Yang, Tian, Liqing, Jiang, Taijiao
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041821/
https://www.ncbi.nlm.nih.gov/pubmed/21365008
http://dx.doi.org/10.1371/journal.pone.0017215
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author Hu, Yun
Dong, Xiaoxi
Wu, Aiping
Cao, Yang
Tian, Liqing
Jiang, Taijiao
author_facet Hu, Yun
Dong, Xiaoxi
Wu, Aiping
Cao, Yang
Tian, Liqing
Jiang, Taijiao
author_sort Hu, Yun
collection PubMed
description Fold recognition, or threading, is a popular protein structure modeling approach that uses known structure templates to build structures for those of unknown. The key to the success of fold recognition methods lies in the proper integration of sequence, physiochemical and structural information. Here we introduce another type of information, local structural preference potentials of 3-residue and 9-residue fragments, for fold recognition. By combining the two local structural preference potentials with the widely used sequence profile, secondary structure information and hydrophobic score, we have developed a new threading method called FR-t5 (fold recognition by use of 5 terms). In benchmark testings, we have found the consideration of local structural preference potentials in FR-t5 not only greatly enhances the alignment accuracy and recognition sensitivity, but also significantly improves the quality of prediction models.
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spelling pubmed-30418212011-03-01 Incorporation of Local Structural Preference Potential Improves Fold Recognition Hu, Yun Dong, Xiaoxi Wu, Aiping Cao, Yang Tian, Liqing Jiang, Taijiao PLoS One Research Article Fold recognition, or threading, is a popular protein structure modeling approach that uses known structure templates to build structures for those of unknown. The key to the success of fold recognition methods lies in the proper integration of sequence, physiochemical and structural information. Here we introduce another type of information, local structural preference potentials of 3-residue and 9-residue fragments, for fold recognition. By combining the two local structural preference potentials with the widely used sequence profile, secondary structure information and hydrophobic score, we have developed a new threading method called FR-t5 (fold recognition by use of 5 terms). In benchmark testings, we have found the consideration of local structural preference potentials in FR-t5 not only greatly enhances the alignment accuracy and recognition sensitivity, but also significantly improves the quality of prediction models. Public Library of Science 2011-02-18 /pmc/articles/PMC3041821/ /pubmed/21365008 http://dx.doi.org/10.1371/journal.pone.0017215 Text en Hu 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
Hu, Yun
Dong, Xiaoxi
Wu, Aiping
Cao, Yang
Tian, Liqing
Jiang, Taijiao
Incorporation of Local Structural Preference Potential Improves Fold Recognition
title Incorporation of Local Structural Preference Potential Improves Fold Recognition
title_full Incorporation of Local Structural Preference Potential Improves Fold Recognition
title_fullStr Incorporation of Local Structural Preference Potential Improves Fold Recognition
title_full_unstemmed Incorporation of Local Structural Preference Potential Improves Fold Recognition
title_short Incorporation of Local Structural Preference Potential Improves Fold Recognition
title_sort incorporation of local structural preference potential improves fold recognition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041821/
https://www.ncbi.nlm.nih.gov/pubmed/21365008
http://dx.doi.org/10.1371/journal.pone.0017215
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