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Scoring Function Based on Weighted Residue Network

Molecular docking is an important method for the research of protein-protein interaction and recognition. A protein can be considered as a network when the residues are treated as its nodes. With the contact energy between residues as link weight, a weighted residue network is constructed in this pa...

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Autores principales: Jiao, Xiong, Chang, Shan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3257100/
https://www.ncbi.nlm.nih.gov/pubmed/22272103
http://dx.doi.org/10.3390/ijms12128773
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author Jiao, Xiong
Chang, Shan
author_facet Jiao, Xiong
Chang, Shan
author_sort Jiao, Xiong
collection PubMed
description Molecular docking is an important method for the research of protein-protein interaction and recognition. A protein can be considered as a network when the residues are treated as its nodes. With the contact energy between residues as link weight, a weighted residue network is constructed in this paper. Two weighted parameters (strength and weighted average nearest neighbors’ degree) are introduced into this model at the same time. The stability of a protein is characterized by its strength. The global topological properties of the protein-protein complex are reflected by the weighted average nearest neighbors’ degree. Based on this weighted network model and these two parameters, a new docking scoring function is proposed in this paper. The scoring and ranking for 42 systems’ bound and unbounded docking results are performed with this new scoring function. Comparing the results obtained from this new scoring function with that from the pair potentials scoring function, we found that this new scoring function has a similar performance to the pair potentials on some items, and this new scoring function can get a better success rate. The calculation of this new scoring function is easy, and the result of its scoring and ranking is acceptable. This work can help us better understand the mechanisms of protein-protein interactions and recognition.
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spelling pubmed-32571002012-01-23 Scoring Function Based on Weighted Residue Network Jiao, Xiong Chang, Shan Int J Mol Sci Article Molecular docking is an important method for the research of protein-protein interaction and recognition. A protein can be considered as a network when the residues are treated as its nodes. With the contact energy between residues as link weight, a weighted residue network is constructed in this paper. Two weighted parameters (strength and weighted average nearest neighbors’ degree) are introduced into this model at the same time. The stability of a protein is characterized by its strength. The global topological properties of the protein-protein complex are reflected by the weighted average nearest neighbors’ degree. Based on this weighted network model and these two parameters, a new docking scoring function is proposed in this paper. The scoring and ranking for 42 systems’ bound and unbounded docking results are performed with this new scoring function. Comparing the results obtained from this new scoring function with that from the pair potentials scoring function, we found that this new scoring function has a similar performance to the pair potentials on some items, and this new scoring function can get a better success rate. The calculation of this new scoring function is easy, and the result of its scoring and ranking is acceptable. This work can help us better understand the mechanisms of protein-protein interactions and recognition. Molecular Diversity Preservation International (MDPI) 2011-12-02 /pmc/articles/PMC3257100/ /pubmed/22272103 http://dx.doi.org/10.3390/ijms12128773 Text en © 2011 by the authors; licensee MDPI, 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
Jiao, Xiong
Chang, Shan
Scoring Function Based on Weighted Residue Network
title Scoring Function Based on Weighted Residue Network
title_full Scoring Function Based on Weighted Residue Network
title_fullStr Scoring Function Based on Weighted Residue Network
title_full_unstemmed Scoring Function Based on Weighted Residue Network
title_short Scoring Function Based on Weighted Residue Network
title_sort scoring function based on weighted residue network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3257100/
https://www.ncbi.nlm.nih.gov/pubmed/22272103
http://dx.doi.org/10.3390/ijms12128773
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AT changshan scoringfunctionbasedonweightedresiduenetwork