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(PS)(2)-v2: template-based protein structure prediction server

BACKGROUND: Template selection and target-template alignment are critical steps for template-based modeling (TBM) methods. To identify the template for the twilight zone of 15~25% sequence similarity between targets and templates is still difficulty for template-based protein structure prediction. T...

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Autores principales: Chen, Chih-Chieh, Hwang, Jenn-Kang, Yang, Jinn-Moon
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775752/
https://www.ncbi.nlm.nih.gov/pubmed/19878598
http://dx.doi.org/10.1186/1471-2105-10-366
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author Chen, Chih-Chieh
Hwang, Jenn-Kang
Yang, Jinn-Moon
author_facet Chen, Chih-Chieh
Hwang, Jenn-Kang
Yang, Jinn-Moon
author_sort Chen, Chih-Chieh
collection PubMed
description BACKGROUND: Template selection and target-template alignment are critical steps for template-based modeling (TBM) methods. To identify the template for the twilight zone of 15~25% sequence similarity between targets and templates is still difficulty for template-based protein structure prediction. This study presents the (PS)(2)-v2 server, based on our original server with numerous enhancements and modifications, to improve reliability and applicability. RESULTS: To detect homologous proteins with remote similarity, the (PS)(2)-v2 server utilizes the S2A2 matrix, which is a 60 × 60 substitution matrix using the secondary structure propensities of 20 amino acids, and the position-specific sequence profile (PSSM) generated by PSI-BLAST. In addition, our server uses multiple templates and multiple models to build and assess models. Our method was evaluated on the Lindahl benchmark for fold recognition and ProSup benchmark for sequence alignment. Evaluation results indicated that our method outperforms sequence-profile approaches, and had comparable performance to that of structure-based methods on these benchmarks. Finally, we tested our method using the 154 TBM targets of the CASP8 (Critical Assessment of Techniques for Protein Structure Prediction) dataset. Experimental results show that (PS)(2)-v2 is ranked 6(th )among 72 severs and is faster than the top-rank five serves, which utilize ab initio methods. CONCLUSION: Experimental results demonstrate that (PS)(2)-v2 with the S2A2 matrix is useful for template selections and target-template alignments by blending the amino acid and structural propensities. The multiple-template and multiple-model strategies are able to significantly improve the accuracies for target-template alignments in the twilight zone. We believe that this server is useful in structure prediction and modeling, especially in detecting homologous templates with sequence similarity in the twilight zone.
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spelling pubmed-27757522009-11-11 (PS)(2)-v2: template-based protein structure prediction server Chen, Chih-Chieh Hwang, Jenn-Kang Yang, Jinn-Moon BMC Bioinformatics Methodology Article BACKGROUND: Template selection and target-template alignment are critical steps for template-based modeling (TBM) methods. To identify the template for the twilight zone of 15~25% sequence similarity between targets and templates is still difficulty for template-based protein structure prediction. This study presents the (PS)(2)-v2 server, based on our original server with numerous enhancements and modifications, to improve reliability and applicability. RESULTS: To detect homologous proteins with remote similarity, the (PS)(2)-v2 server utilizes the S2A2 matrix, which is a 60 × 60 substitution matrix using the secondary structure propensities of 20 amino acids, and the position-specific sequence profile (PSSM) generated by PSI-BLAST. In addition, our server uses multiple templates and multiple models to build and assess models. Our method was evaluated on the Lindahl benchmark for fold recognition and ProSup benchmark for sequence alignment. Evaluation results indicated that our method outperforms sequence-profile approaches, and had comparable performance to that of structure-based methods on these benchmarks. Finally, we tested our method using the 154 TBM targets of the CASP8 (Critical Assessment of Techniques for Protein Structure Prediction) dataset. Experimental results show that (PS)(2)-v2 is ranked 6(th )among 72 severs and is faster than the top-rank five serves, which utilize ab initio methods. CONCLUSION: Experimental results demonstrate that (PS)(2)-v2 with the S2A2 matrix is useful for template selections and target-template alignments by blending the amino acid and structural propensities. The multiple-template and multiple-model strategies are able to significantly improve the accuracies for target-template alignments in the twilight zone. We believe that this server is useful in structure prediction and modeling, especially in detecting homologous templates with sequence similarity in the twilight zone. BioMed Central 2009-10-31 /pmc/articles/PMC2775752/ /pubmed/19878598 http://dx.doi.org/10.1186/1471-2105-10-366 Text en Copyright © 2009 Chen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Chen, Chih-Chieh
Hwang, Jenn-Kang
Yang, Jinn-Moon
(PS)(2)-v2: template-based protein structure prediction server
title (PS)(2)-v2: template-based protein structure prediction server
title_full (PS)(2)-v2: template-based protein structure prediction server
title_fullStr (PS)(2)-v2: template-based protein structure prediction server
title_full_unstemmed (PS)(2)-v2: template-based protein structure prediction server
title_short (PS)(2)-v2: template-based protein structure prediction server
title_sort (ps)(2)-v2: template-based protein structure prediction server
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775752/
https://www.ncbi.nlm.nih.gov/pubmed/19878598
http://dx.doi.org/10.1186/1471-2105-10-366
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