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A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11
BACKGROUND: With more and more protein sequences produced in the genomic era, predicting protein structures from sequences becomes very important for elucidating the molecular details and functions of these proteins for biomedical research. Traditional template-based protein structure prediction met...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619059/ https://www.ncbi.nlm.nih.gov/pubmed/26493701 http://dx.doi.org/10.1186/s12859-015-0775-x |
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author | Li, Jilong Cao, Renzhi Cheng, Jianlin |
author_facet | Li, Jilong Cao, Renzhi Cheng, Jianlin |
author_sort | Li, Jilong |
collection | PubMed |
description | BACKGROUND: With more and more protein sequences produced in the genomic era, predicting protein structures from sequences becomes very important for elucidating the molecular details and functions of these proteins for biomedical research. Traditional template-based protein structure prediction methods tend to focus on identifying the best templates, generating the best alignments, and applying the best energy function to rank models, which often cannot achieve the best performance because of the difficulty of obtaining best templates, alignments, and models. METHODS: We developed a large-scale conformation sampling and evaluation method and its servers to improve the reliability and robustness of protein structure prediction. In the first step, our method used a variety of alignment methods to sample relevant and complementary templates and to generate alternative and diverse target-template alignments, used a template and alignment combination protocol to combine alignments, and used template-based and template-free modeling methods to generate a pool of conformations for a target protein. In the second step, it used a large number of protein model quality assessment methods to evaluate and rank the models in the protein model pool, in conjunction with an exception handling strategy to deal with any additional failure in model ranking. RESULTS: The method was implemented as two protein structure prediction servers: MULTICOM-CONSTRUCT and MULTICOM-CLUSTER that participated in the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) in 2014. The two servers were ranked among the best 10 server predictors. CONCLUSIONS: The good performance of our servers in CASP11 demonstrates the effectiveness and robustness of the large-scale conformation sampling and evaluation. The MULTICOM server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0775-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4619059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46190592015-10-25 A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 Li, Jilong Cao, Renzhi Cheng, Jianlin BMC Bioinformatics Research Article BACKGROUND: With more and more protein sequences produced in the genomic era, predicting protein structures from sequences becomes very important for elucidating the molecular details and functions of these proteins for biomedical research. Traditional template-based protein structure prediction methods tend to focus on identifying the best templates, generating the best alignments, and applying the best energy function to rank models, which often cannot achieve the best performance because of the difficulty of obtaining best templates, alignments, and models. METHODS: We developed a large-scale conformation sampling and evaluation method and its servers to improve the reliability and robustness of protein structure prediction. In the first step, our method used a variety of alignment methods to sample relevant and complementary templates and to generate alternative and diverse target-template alignments, used a template and alignment combination protocol to combine alignments, and used template-based and template-free modeling methods to generate a pool of conformations for a target protein. In the second step, it used a large number of protein model quality assessment methods to evaluate and rank the models in the protein model pool, in conjunction with an exception handling strategy to deal with any additional failure in model ranking. RESULTS: The method was implemented as two protein structure prediction servers: MULTICOM-CONSTRUCT and MULTICOM-CLUSTER that participated in the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) in 2014. The two servers were ranked among the best 10 server predictors. CONCLUSIONS: The good performance of our servers in CASP11 demonstrates the effectiveness and robustness of the large-scale conformation sampling and evaluation. The MULTICOM server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0775-x) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-23 /pmc/articles/PMC4619059/ /pubmed/26493701 http://dx.doi.org/10.1186/s12859-015-0775-x Text en © Li et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Li, Jilong Cao, Renzhi Cheng, Jianlin A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 |
title | A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 |
title_full | A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 |
title_fullStr | A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 |
title_full_unstemmed | A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 |
title_short | A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11 |
title_sort | large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in casp11 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619059/ https://www.ncbi.nlm.nih.gov/pubmed/26493701 http://dx.doi.org/10.1186/s12859-015-0775-x |
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