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Protein docking prediction using predicted protein-protein interface

BACKGROUND: Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex stru...

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Detalles Bibliográficos
Autores principales: Li, Bin, Kihara, Daisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287255/
https://www.ncbi.nlm.nih.gov/pubmed/22233443
http://dx.doi.org/10.1186/1471-2105-13-7
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author Li, Bin
Kihara, Daisuke
author_facet Li, Bin
Kihara, Daisuke
author_sort Li, Bin
collection PubMed
description BACKGROUND: Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. RESULTS: We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. CONCLUSION: We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.
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spelling pubmed-32872552012-02-28 Protein docking prediction using predicted protein-protein interface Li, Bin Kihara, Daisuke BMC Bioinformatics Research Article BACKGROUND: Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. RESULTS: We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. CONCLUSION: We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases. BioMed Central 2012-01-10 /pmc/articles/PMC3287255/ /pubmed/22233443 http://dx.doi.org/10.1186/1471-2105-13-7 Text en Copyright ©2012 Li and Kihara; 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
Li, Bin
Kihara, Daisuke
Protein docking prediction using predicted protein-protein interface
title Protein docking prediction using predicted protein-protein interface
title_full Protein docking prediction using predicted protein-protein interface
title_fullStr Protein docking prediction using predicted protein-protein interface
title_full_unstemmed Protein docking prediction using predicted protein-protein interface
title_short Protein docking prediction using predicted protein-protein interface
title_sort protein docking prediction using predicted protein-protein interface
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287255/
https://www.ncbi.nlm.nih.gov/pubmed/22233443
http://dx.doi.org/10.1186/1471-2105-13-7
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