Cargando…

How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction

In many protein-protein docking algorithms, binding site information is used to help predicting the protein complex structures. Using correct and accurate binding site information can increase protein-protein docking success rate significantly. On the other hand, using wrong binding sites informatio...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Lin, Huang, Yanzhao, Xiao, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3790831/
https://www.ncbi.nlm.nih.gov/pubmed/24124522
http://dx.doi.org/10.1371/journal.pone.0075936
_version_ 1782286656996376576
author Li, Lin
Huang, Yanzhao
Xiao, Yi
author_facet Li, Lin
Huang, Yanzhao
Xiao, Yi
author_sort Li, Lin
collection PubMed
description In many protein-protein docking algorithms, binding site information is used to help predicting the protein complex structures. Using correct and accurate binding site information can increase protein-protein docking success rate significantly. On the other hand, using wrong binding sites information should lead to a failed prediction, or, at least decrease the success rate. Recently, various successful theoretical methods have been proposed to predict the binding sites of proteins. However, the predicted binding site information is not always reliable, sometimes wrong binding site information could be given. Hence there is a high risk to use the predicted binding site information in current docking algorithms. In this paper, a softly restricting method (SRM) is developed to solve this problem. By utilizing predicted binding site information in a proper way, the SRM algorithm is sensitive to the correct binding site information but insensitive to wrong information, which decreases the risk of using predicted binding site information. This SRM is tested on benchmark 3.0 using purely predicted binding site information. The result shows that when the predicted information is correct, SRM increases the success rate significantly; however, even if the predicted information is completely wrong, SRM only decreases success rate slightly, which indicates that the SRM is suitable for utilizing predicted binding site information.
format Online
Article
Text
id pubmed-3790831
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-37908312013-10-11 How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction Li, Lin Huang, Yanzhao Xiao, Yi PLoS One Research Article In many protein-protein docking algorithms, binding site information is used to help predicting the protein complex structures. Using correct and accurate binding site information can increase protein-protein docking success rate significantly. On the other hand, using wrong binding sites information should lead to a failed prediction, or, at least decrease the success rate. Recently, various successful theoretical methods have been proposed to predict the binding sites of proteins. However, the predicted binding site information is not always reliable, sometimes wrong binding site information could be given. Hence there is a high risk to use the predicted binding site information in current docking algorithms. In this paper, a softly restricting method (SRM) is developed to solve this problem. By utilizing predicted binding site information in a proper way, the SRM algorithm is sensitive to the correct binding site information but insensitive to wrong information, which decreases the risk of using predicted binding site information. This SRM is tested on benchmark 3.0 using purely predicted binding site information. The result shows that when the predicted information is correct, SRM increases the success rate significantly; however, even if the predicted information is completely wrong, SRM only decreases success rate slightly, which indicates that the SRM is suitable for utilizing predicted binding site information. Public Library of Science 2013-10-04 /pmc/articles/PMC3790831/ /pubmed/24124522 http://dx.doi.org/10.1371/journal.pone.0075936 Text en © 2013 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Li, Lin
Huang, Yanzhao
Xiao, Yi
How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction
title How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction
title_full How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction
title_fullStr How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction
title_full_unstemmed How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction
title_short How to Use Not-Always-Reliable Binding Site Information in Protein-Protein Docking Prediction
title_sort how to use not-always-reliable binding site information in protein-protein docking prediction
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3790831/
https://www.ncbi.nlm.nih.gov/pubmed/24124522
http://dx.doi.org/10.1371/journal.pone.0075936
work_keys_str_mv AT lilin howtousenotalwaysreliablebindingsiteinformationinproteinproteindockingprediction
AT huangyanzhao howtousenotalwaysreliablebindingsiteinformationinproteinproteindockingprediction
AT xiaoyi howtousenotalwaysreliablebindingsiteinformationinproteinproteindockingprediction