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ConEVA: a toolbox for comprehensive assessment of protein contacts
BACKGROUND: In recent years, successful contact prediction methods and contact-guided ab initio protein structure prediction methods have highlighted the importance of incorporating contact information into protein structure prediction methods. It is also observed that for almost all globular protei...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5142288/ https://www.ncbi.nlm.nih.gov/pubmed/27923350 http://dx.doi.org/10.1186/s12859-016-1404-z |
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author | Adhikari, Badri Nowotny, Jackson Bhattacharya, Debswapna Hou, Jie Cheng, Jianlin |
author_facet | Adhikari, Badri Nowotny, Jackson Bhattacharya, Debswapna Hou, Jie Cheng, Jianlin |
author_sort | Adhikari, Badri |
collection | PubMed |
description | BACKGROUND: In recent years, successful contact prediction methods and contact-guided ab initio protein structure prediction methods have highlighted the importance of incorporating contact information into protein structure prediction methods. It is also observed that for almost all globular proteins, the quality of contact prediction dictates the accuracy of structure prediction. Hence, like many existing evaluation measures for evaluating 3D protein models, various measures are currently used to evaluate predicted contacts, with the most popular ones being precision, coverage and distance distribution score (X(d)). RESULTS: We have built a web application and a downloadable tool, ConEVA, for comprehensive assessment and detailed comparison of predicted contacts. Besides implementing existing measures for contact evaluation we have implemented new and useful methods of contact visualization using chord diagrams and comparison using Jaccard similarity computations. For a set (or sets) of predicted contacts, the web application runs even when a native structure is not available, visualizing the contact coverage and similarity between predicted contacts. We applied the tool on various contact prediction data sets and present our findings and insights we obtained from the evaluation of effective contact assessments. ConEVA is publicly available at http://cactus.rnet.missouri.edu/coneva/. CONCLUSION: ConEVA is useful for a range of contact related analysis and evaluations including predicted contact comparison, investigation of individual protein folding using predicted contacts, and analysis of contacts in a structure of interest. |
format | Online Article Text |
id | pubmed-5142288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-51422882016-12-15 ConEVA: a toolbox for comprehensive assessment of protein contacts Adhikari, Badri Nowotny, Jackson Bhattacharya, Debswapna Hou, Jie Cheng, Jianlin BMC Bioinformatics Software BACKGROUND: In recent years, successful contact prediction methods and contact-guided ab initio protein structure prediction methods have highlighted the importance of incorporating contact information into protein structure prediction methods. It is also observed that for almost all globular proteins, the quality of contact prediction dictates the accuracy of structure prediction. Hence, like many existing evaluation measures for evaluating 3D protein models, various measures are currently used to evaluate predicted contacts, with the most popular ones being precision, coverage and distance distribution score (X(d)). RESULTS: We have built a web application and a downloadable tool, ConEVA, for comprehensive assessment and detailed comparison of predicted contacts. Besides implementing existing measures for contact evaluation we have implemented new and useful methods of contact visualization using chord diagrams and comparison using Jaccard similarity computations. For a set (or sets) of predicted contacts, the web application runs even when a native structure is not available, visualizing the contact coverage and similarity between predicted contacts. We applied the tool on various contact prediction data sets and present our findings and insights we obtained from the evaluation of effective contact assessments. ConEVA is publicly available at http://cactus.rnet.missouri.edu/coneva/. CONCLUSION: ConEVA is useful for a range of contact related analysis and evaluations including predicted contact comparison, investigation of individual protein folding using predicted contacts, and analysis of contacts in a structure of interest. BioMed Central 2016-12-07 /pmc/articles/PMC5142288/ /pubmed/27923350 http://dx.doi.org/10.1186/s12859-016-1404-z Text en © The Author(s). 2016 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 | Software Adhikari, Badri Nowotny, Jackson Bhattacharya, Debswapna Hou, Jie Cheng, Jianlin ConEVA: a toolbox for comprehensive assessment of protein contacts |
title | ConEVA: a toolbox for comprehensive assessment of protein contacts |
title_full | ConEVA: a toolbox for comprehensive assessment of protein contacts |
title_fullStr | ConEVA: a toolbox for comprehensive assessment of protein contacts |
title_full_unstemmed | ConEVA: a toolbox for comprehensive assessment of protein contacts |
title_short | ConEVA: a toolbox for comprehensive assessment of protein contacts |
title_sort | coneva: a toolbox for comprehensive assessment of protein contacts |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5142288/ https://www.ncbi.nlm.nih.gov/pubmed/27923350 http://dx.doi.org/10.1186/s12859-016-1404-z |
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