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Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines

As a chronic disorder, insomnia affects approximately 10% of the population at some time during their lives, and its treatment is often challenging. Since the antagonists of the H(1) receptor, a protein prevalent in human central nervous system, have been proven as effective therapeutic agents for t...

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Autores principales: Yang, Yinfeng, Li, Yan, Pan, Yanqiu, Wang, Jinghui, Lin, Feng, Wang, Chao, Zhang, Shuwei, Yang, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4730370/
https://www.ncbi.nlm.nih.gov/pubmed/26797608
http://dx.doi.org/10.3390/ijms17010129
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author Yang, Yinfeng
Li, Yan
Pan, Yanqiu
Wang, Jinghui
Lin, Feng
Wang, Chao
Zhang, Shuwei
Yang, Ling
author_facet Yang, Yinfeng
Li, Yan
Pan, Yanqiu
Wang, Jinghui
Lin, Feng
Wang, Chao
Zhang, Shuwei
Yang, Ling
author_sort Yang, Yinfeng
collection PubMed
description As a chronic disorder, insomnia affects approximately 10% of the population at some time during their lives, and its treatment is often challenging. Since the antagonists of the H(1) receptor, a protein prevalent in human central nervous system, have been proven as effective therapeutic agents for treating insomnia, the H(1) receptor is quite possibly a promising target for developing potent anti-insomnia drugs. For the purpose of understanding the structural actors affecting the antagonism potency, presently a theoretical research of molecular interactions between 129 molecules and the H(1) receptor is performed through three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. The ligand-based comparative molecular similarity indices analysis (CoMSIA) model (Q(2) = 0.525, R(2)(ncv) = 0.891, R(2)(pred) = 0.807) has good quality for predicting the bioactivities of new chemicals. The cross-validated result suggests that the developed models have excellent internal and external predictability and consistency. The obtained contour maps were appraised for affinity trends for the investigated compounds, which provides significantly useful information in the rational drug design of novel anti-insomnia agents. Molecular docking was also performed to investigate the mode of interaction between the ligand and the active site of the receptor. Furthermore, as a supplementary tool to study the docking conformation of the antagonists in the H(1) receptor binding pocket, molecular dynamics simulation was also applied, providing insights into the changes in the structure. All of the models and the derived information would, we hope, be of help for developing novel potent histamine H(1) receptor antagonists, as well as exploring the H(1)-antihistamines interaction mechanism.
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spelling pubmed-47303702016-02-11 Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines Yang, Yinfeng Li, Yan Pan, Yanqiu Wang, Jinghui Lin, Feng Wang, Chao Zhang, Shuwei Yang, Ling Int J Mol Sci Article As a chronic disorder, insomnia affects approximately 10% of the population at some time during their lives, and its treatment is often challenging. Since the antagonists of the H(1) receptor, a protein prevalent in human central nervous system, have been proven as effective therapeutic agents for treating insomnia, the H(1) receptor is quite possibly a promising target for developing potent anti-insomnia drugs. For the purpose of understanding the structural actors affecting the antagonism potency, presently a theoretical research of molecular interactions between 129 molecules and the H(1) receptor is performed through three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. The ligand-based comparative molecular similarity indices analysis (CoMSIA) model (Q(2) = 0.525, R(2)(ncv) = 0.891, R(2)(pred) = 0.807) has good quality for predicting the bioactivities of new chemicals. The cross-validated result suggests that the developed models have excellent internal and external predictability and consistency. The obtained contour maps were appraised for affinity trends for the investigated compounds, which provides significantly useful information in the rational drug design of novel anti-insomnia agents. Molecular docking was also performed to investigate the mode of interaction between the ligand and the active site of the receptor. Furthermore, as a supplementary tool to study the docking conformation of the antagonists in the H(1) receptor binding pocket, molecular dynamics simulation was also applied, providing insights into the changes in the structure. All of the models and the derived information would, we hope, be of help for developing novel potent histamine H(1) receptor antagonists, as well as exploring the H(1)-antihistamines interaction mechanism. MDPI 2016-01-19 /pmc/articles/PMC4730370/ /pubmed/26797608 http://dx.doi.org/10.3390/ijms17010129 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Yinfeng
Li, Yan
Pan, Yanqiu
Wang, Jinghui
Lin, Feng
Wang, Chao
Zhang, Shuwei
Yang, Ling
Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines
title Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines
title_full Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines
title_fullStr Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines
title_full_unstemmed Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines
title_short Computational Analysis of Structure-Based Interactions for Novel H(1)-Antihistamines
title_sort computational analysis of structure-based interactions for novel h(1)-antihistamines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4730370/
https://www.ncbi.nlm.nih.gov/pubmed/26797608
http://dx.doi.org/10.3390/ijms17010129
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