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ECMIS: computational approach for the identification of hotspots at protein-protein interfaces
BACKGROUND: Various methods have been developed to computationally predict hotspot residues at novel protein-protein interfaces. However, there are various challenges in obtaining accurate prediction. We have developed a novel method which uses different aspects of protein structure and sequence spa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177600/ https://www.ncbi.nlm.nih.gov/pubmed/25228146 http://dx.doi.org/10.1186/1471-2105-15-303 |
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author | Shingate, Prashant Manoharan, Malini Sukhwal, Anshul Sowdhamini, Ramanathan |
author_facet | Shingate, Prashant Manoharan, Malini Sukhwal, Anshul Sowdhamini, Ramanathan |
author_sort | Shingate, Prashant |
collection | PubMed |
description | BACKGROUND: Various methods have been developed to computationally predict hotspot residues at novel protein-protein interfaces. However, there are various challenges in obtaining accurate prediction. We have developed a novel method which uses different aspects of protein structure and sequence space at residue level to highlight interface residues crucial for the protein-protein complex formation. RESULTS: ECMIS (Energetic Conservation Mass Index and Spatial Clustering) algorithm was able to outperform existing hotspot identification methods. It was able to achieve around 80% accuracy with incredible increase in sensitivity and outperforms other existing methods. This method is even sensitive towards the hotspot residues contributing only small-scale hydrophobic interactions. CONCLUSION: Combination of diverse features of the protein viz. energy contribution, extent of conservation, location and surrounding environment, along with optimized weightage for each feature, was the key for the success of the algorithm. The academic version of the algorithm is available at http://caps.ncbs.res.in/download/ECMIS/ECMIS.zip. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-303) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4177600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41776002014-09-29 ECMIS: computational approach for the identification of hotspots at protein-protein interfaces Shingate, Prashant Manoharan, Malini Sukhwal, Anshul Sowdhamini, Ramanathan BMC Bioinformatics Research Article BACKGROUND: Various methods have been developed to computationally predict hotspot residues at novel protein-protein interfaces. However, there are various challenges in obtaining accurate prediction. We have developed a novel method which uses different aspects of protein structure and sequence space at residue level to highlight interface residues crucial for the protein-protein complex formation. RESULTS: ECMIS (Energetic Conservation Mass Index and Spatial Clustering) algorithm was able to outperform existing hotspot identification methods. It was able to achieve around 80% accuracy with incredible increase in sensitivity and outperforms other existing methods. This method is even sensitive towards the hotspot residues contributing only small-scale hydrophobic interactions. CONCLUSION: Combination of diverse features of the protein viz. energy contribution, extent of conservation, location and surrounding environment, along with optimized weightage for each feature, was the key for the success of the algorithm. The academic version of the algorithm is available at http://caps.ncbs.res.in/download/ECMIS/ECMIS.zip. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-303) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-16 /pmc/articles/PMC4177600/ /pubmed/25228146 http://dx.doi.org/10.1186/1471-2105-15-303 Text en © Shingate et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. 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 credited. 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 Shingate, Prashant Manoharan, Malini Sukhwal, Anshul Sowdhamini, Ramanathan ECMIS: computational approach for the identification of hotspots at protein-protein interfaces |
title | ECMIS: computational approach for the identification of hotspots at protein-protein interfaces |
title_full | ECMIS: computational approach for the identification of hotspots at protein-protein interfaces |
title_fullStr | ECMIS: computational approach for the identification of hotspots at protein-protein interfaces |
title_full_unstemmed | ECMIS: computational approach for the identification of hotspots at protein-protein interfaces |
title_short | ECMIS: computational approach for the identification of hotspots at protein-protein interfaces |
title_sort | ecmis: computational approach for the identification of hotspots at protein-protein interfaces |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177600/ https://www.ncbi.nlm.nih.gov/pubmed/25228146 http://dx.doi.org/10.1186/1471-2105-15-303 |
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