SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.

How to recognize the structural fold of a protein is one of the challenges in protein structure prediction. We have developed a series of single (non-consensus) methods (SPARKS, SP(2), SP(3), SP(4)) that are based on weighted matching of two to four sequence and structure-based profiles. There is a...

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Autores principales:	Wei Zhang, Song Liu, Yaoqi Zhou
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2008
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/35750ca23b0b4192a369b776da1e0d2b
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spelling	oai:doaj.org-article:35750ca23b0b4192a369b776da1e0d2b2021-11-25T06:12:13ZSP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.1932-620310.1371/journal.pone.0002325https://doaj.org/article/35750ca23b0b4192a369b776da1e0d2b2008-06-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18523556/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203How to recognize the structural fold of a protein is one of the challenges in protein structure prediction. We have developed a series of single (non-consensus) methods (SPARKS, SP(2), SP(3), SP(4)) that are based on weighted matching of two to four sequence and structure-based profiles. There is a robust improvement of the accuracy and sensitivity of fold recognition as the number of matching profiles increases. Here, we introduce a new profile-profile comparison term based on real-value dihedral torsion angles. Together with updated real-value solvent accessibility profile and a new variable gap-penalty model based on fractional power of insertion/deletion profiles, the new method (SP(5)) leads to a robust improvement over previous SP method. There is a 2% absolute increase (5% relative improvement) in alignment accuracy over SP(4) based on two independent benchmarks. Moreover, SP(5) makes 7% absolute increase (22% relative improvement) in success rate of recognizing correct structural folds, and 32% relative improvement in model accuracy of models within the same fold in Lindahl benchmark. In addition, modeling accuracy of top-1 ranked models is improved by 12% over SP(4) for the difficult targets in CASP 7 test set. These results highlight the importance of harnessing predicted structural properties in challenging remote-homolog recognition. The SP(5) server is available at http://sparks.informatics.iupui.edu.Wei ZhangSong LiuYaoqi ZhouPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 3, Iss 6, p e2325 (2008)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wei Zhang Song Liu Yaoqi Zhou SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
description	How to recognize the structural fold of a protein is one of the challenges in protein structure prediction. We have developed a series of single (non-consensus) methods (SPARKS, SP(2), SP(3), SP(4)) that are based on weighted matching of two to four sequence and structure-based profiles. There is a robust improvement of the accuracy and sensitivity of fold recognition as the number of matching profiles increases. Here, we introduce a new profile-profile comparison term based on real-value dihedral torsion angles. Together with updated real-value solvent accessibility profile and a new variable gap-penalty model based on fractional power of insertion/deletion profiles, the new method (SP(5)) leads to a robust improvement over previous SP method. There is a 2% absolute increase (5% relative improvement) in alignment accuracy over SP(4) based on two independent benchmarks. Moreover, SP(5) makes 7% absolute increase (22% relative improvement) in success rate of recognizing correct structural folds, and 32% relative improvement in model accuracy of models within the same fold in Lindahl benchmark. In addition, modeling accuracy of top-1 ranked models is improved by 12% over SP(4) for the difficult targets in CASP 7 test set. These results highlight the importance of harnessing predicted structural properties in challenging remote-homolog recognition. The SP(5) server is available at http://sparks.informatics.iupui.edu.
format	article
author	Wei Zhang Song Liu Yaoqi Zhou
author_facet	Wei Zhang Song Liu Yaoqi Zhou
author_sort	Wei Zhang
title	SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
title_short	SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
title_full	SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
title_fullStr	SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
title_full_unstemmed	SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
title_sort	sp5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.
publisher	Public Library of Science (PLoS)
publishDate	2008
url	https://doaj.org/article/35750ca23b0b4192a369b776da1e0d2b
work_keys_str_mv	AT weizhang sp5improvingproteinfoldrecognitionbyusingtorsionangleprofilesandprofilebasedgappenaltymodel AT songliu sp5improvingproteinfoldrecognitionbyusingtorsionangleprofilesandprofilebasedgappenaltymodel AT yaoqizhou sp5improvingproteinfoldrecognitionbyusingtorsionangleprofilesandprofilebasedgappenaltymodel
_version_	1718414034605178880

SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model.

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