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Ensemble approach to predict specificity determinants: benchmarking and validation
BACKGROUND: It is extremely important and challenging to identify the sites that are responsible for functional specification or diversification in protein families. In this study, a rigorous comparative benchmarking protocol was employed to provide a reliable evaluation of methods which predict the...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2716344/ https://www.ncbi.nlm.nih.gov/pubmed/19573245 http://dx.doi.org/10.1186/1471-2105-10-207 |
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author | Chakrabarti, Saikat Panchenko, Anna R |
author_facet | Chakrabarti, Saikat Panchenko, Anna R |
author_sort | Chakrabarti, Saikat |
collection | PubMed |
description | BACKGROUND: It is extremely important and challenging to identify the sites that are responsible for functional specification or diversification in protein families. In this study, a rigorous comparative benchmarking protocol was employed to provide a reliable evaluation of methods which predict the specificity determining sites. Subsequently, three best performing methods were applied to identify new potential specificity determining sites through ensemble approach and common agreement of their prediction results. RESULTS: It was shown that the analysis of structural characteristics of predicted specificity determining sites might provide the means to validate their prediction accuracy. For example, we found that for smaller distances it holds true that the more reliable the prediction method is, the closer predicted specificity determining sites are to each other and to the ligand. CONCLUSION: We observed certain similarities of structural features between predicted and actual subsites which might point to their functional relevance. We speculate that majority of the identified potential specificity determining sites might be indirectly involved in specific interactions and could be ideal target for mutagenesis experiments. |
format | Text |
id | pubmed-2716344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27163442009-07-28 Ensemble approach to predict specificity determinants: benchmarking and validation Chakrabarti, Saikat Panchenko, Anna R BMC Bioinformatics Research Article BACKGROUND: It is extremely important and challenging to identify the sites that are responsible for functional specification or diversification in protein families. In this study, a rigorous comparative benchmarking protocol was employed to provide a reliable evaluation of methods which predict the specificity determining sites. Subsequently, three best performing methods were applied to identify new potential specificity determining sites through ensemble approach and common agreement of their prediction results. RESULTS: It was shown that the analysis of structural characteristics of predicted specificity determining sites might provide the means to validate their prediction accuracy. For example, we found that for smaller distances it holds true that the more reliable the prediction method is, the closer predicted specificity determining sites are to each other and to the ligand. CONCLUSION: We observed certain similarities of structural features between predicted and actual subsites which might point to their functional relevance. We speculate that majority of the identified potential specificity determining sites might be indirectly involved in specific interactions and could be ideal target for mutagenesis experiments. BioMed Central 2009-07-02 /pmc/articles/PMC2716344/ /pubmed/19573245 http://dx.doi.org/10.1186/1471-2105-10-207 Text en Copyright © 2009 Chakrabarti and Panchenko; 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 | Research Article Chakrabarti, Saikat Panchenko, Anna R Ensemble approach to predict specificity determinants: benchmarking and validation |
title | Ensemble approach to predict specificity determinants: benchmarking and validation |
title_full | Ensemble approach to predict specificity determinants: benchmarking and validation |
title_fullStr | Ensemble approach to predict specificity determinants: benchmarking and validation |
title_full_unstemmed | Ensemble approach to predict specificity determinants: benchmarking and validation |
title_short | Ensemble approach to predict specificity determinants: benchmarking and validation |
title_sort | ensemble approach to predict specificity determinants: benchmarking and validation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2716344/ https://www.ncbi.nlm.nih.gov/pubmed/19573245 http://dx.doi.org/10.1186/1471-2105-10-207 |
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