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Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction

In recent years, although many ligand-binding site prediction methods have been developed, there has still been a great demand to improve the prediction accuracy and compare different prediction algorithms to evaluate their performances. In this work, in order to improve the performance of the prote...

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Detalles Bibliográficos
Autores principales: Gao, Jun, Liu, Qi, Kang, Hong, Cao, Zhiwei, Zhu, Ruixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3430263/
https://www.ncbi.nlm.nih.gov/pubmed/22942732
http://dx.doi.org/10.3390/ijms13078752
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author Gao, Jun
Liu, Qi
Kang, Hong
Cao, Zhiwei
Zhu, Ruixin
author_facet Gao, Jun
Liu, Qi
Kang, Hong
Cao, Zhiwei
Zhu, Ruixin
author_sort Gao, Jun
collection PubMed
description In recent years, although many ligand-binding site prediction methods have been developed, there has still been a great demand to improve the prediction accuracy and compare different prediction algorithms to evaluate their performances. In this work, in order to improve the performance of the protein-ligand binding site prediction method presented in our former study, a comparison of different binding site ranking lists was studied. Four kinds of properties, i.e., pocket size, distance from the protein centroid, sequence conservation and the number of hydrophobic residues, have been chosen as the corresponding ranking criterion respectively. Our studies show that the sequence conservation information helps to rank the real pockets with the most successful accuracy compared to others. At the same time, the pocket size and the distance of binding site from the protein centroid are also found to be helpful. In addition, a multi-view ranking aggregation method, which combines the information among those four properties, was further applied in our study. The results show that a better performance can be achieved by the aggregation of the complementary properties in the prediction of ligand-binding sites.
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spelling pubmed-34302632012-08-31 Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction Gao, Jun Liu, Qi Kang, Hong Cao, Zhiwei Zhu, Ruixin Int J Mol Sci Article In recent years, although many ligand-binding site prediction methods have been developed, there has still been a great demand to improve the prediction accuracy and compare different prediction algorithms to evaluate their performances. In this work, in order to improve the performance of the protein-ligand binding site prediction method presented in our former study, a comparison of different binding site ranking lists was studied. Four kinds of properties, i.e., pocket size, distance from the protein centroid, sequence conservation and the number of hydrophobic residues, have been chosen as the corresponding ranking criterion respectively. Our studies show that the sequence conservation information helps to rank the real pockets with the most successful accuracy compared to others. At the same time, the pocket size and the distance of binding site from the protein centroid are also found to be helpful. In addition, a multi-view ranking aggregation method, which combines the information among those four properties, was further applied in our study. The results show that a better performance can be achieved by the aggregation of the complementary properties in the prediction of ligand-binding sites. Molecular Diversity Preservation International (MDPI) 2012-07-16 /pmc/articles/PMC3430263/ /pubmed/22942732 http://dx.doi.org/10.3390/ijms13078752 Text en © 2012 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Gao, Jun
Liu, Qi
Kang, Hong
Cao, Zhiwei
Zhu, Ruixin
Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction
title Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction
title_full Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction
title_fullStr Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction
title_full_unstemmed Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction
title_short Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction
title_sort comparison of different ranking methods in protein-ligand binding site prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3430263/
https://www.ncbi.nlm.nih.gov/pubmed/22942732
http://dx.doi.org/10.3390/ijms13078752
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