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Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists

The antiandrogens, such as bicalutamide, targeting the androgen receptor (AR), are the main endocrine therapies for prostate cancer (PCa). But as drug resistance to antiandrogens emerges in advanced PCa, there presents a high medical need for exploitation of novel AR antagonists. In this work, the r...

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Autores principales: Wang, Yuwei, Han, Rui, Zhang, Huimin, Liu, Hongli, Li, Jiazhong, Liu, Huanxiang, Gramatica, Paola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5331419/
https://www.ncbi.nlm.nih.gov/pubmed/28293633
http://dx.doi.org/10.1155/2017/3572394
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author Wang, Yuwei
Han, Rui
Zhang, Huimin
Liu, Hongli
Li, Jiazhong
Liu, Huanxiang
Gramatica, Paola
author_facet Wang, Yuwei
Han, Rui
Zhang, Huimin
Liu, Hongli
Li, Jiazhong
Liu, Huanxiang
Gramatica, Paola
author_sort Wang, Yuwei
collection PubMed
description The antiandrogens, such as bicalutamide, targeting the androgen receptor (AR), are the main endocrine therapies for prostate cancer (PCa). But as drug resistance to antiandrogens emerges in advanced PCa, there presents a high medical need for exploitation of novel AR antagonists. In this work, the relationships between the molecular structures and antiandrogenic activities of a series of 7α-substituted dihydrotestosterone derivatives were investigated. The proposed MLR model obtained high predictive ability. The thoroughly validated QSAR model was used to virtually screen new dihydrotestosterones derivatives taken from PubChem, resulting in the finding of novel compounds CID_70128824, CID_70127147, and CID_70126881, whose in silico bioactivities are much higher than the published best one, even higher than bicalutamide. In addition, molecular docking, molecular dynamics (MD) simulations, and MM/GBSA have been employed to analyze and compare the binding modes between the novel compounds and AR. Through the analysis of the binding free energy and residue energy decomposition, we concluded that the newly discovered chemicals can in silico bind to AR with similar position and mechanism to the reported active compound and the van der Waals interaction is the main driving force during the binding process.
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spelling pubmed-53314192017-03-14 Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists Wang, Yuwei Han, Rui Zhang, Huimin Liu, Hongli Li, Jiazhong Liu, Huanxiang Gramatica, Paola Biomed Res Int Research Article The antiandrogens, such as bicalutamide, targeting the androgen receptor (AR), are the main endocrine therapies for prostate cancer (PCa). But as drug resistance to antiandrogens emerges in advanced PCa, there presents a high medical need for exploitation of novel AR antagonists. In this work, the relationships between the molecular structures and antiandrogenic activities of a series of 7α-substituted dihydrotestosterone derivatives were investigated. The proposed MLR model obtained high predictive ability. The thoroughly validated QSAR model was used to virtually screen new dihydrotestosterones derivatives taken from PubChem, resulting in the finding of novel compounds CID_70128824, CID_70127147, and CID_70126881, whose in silico bioactivities are much higher than the published best one, even higher than bicalutamide. In addition, molecular docking, molecular dynamics (MD) simulations, and MM/GBSA have been employed to analyze and compare the binding modes between the novel compounds and AR. Through the analysis of the binding free energy and residue energy decomposition, we concluded that the newly discovered chemicals can in silico bind to AR with similar position and mechanism to the reported active compound and the van der Waals interaction is the main driving force during the binding process. Hindawi Publishing Corporation 2017 2017-02-15 /pmc/articles/PMC5331419/ /pubmed/28293633 http://dx.doi.org/10.1155/2017/3572394 Text en Copyright © 2017 Yuwei Wang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Yuwei
Han, Rui
Zhang, Huimin
Liu, Hongli
Li, Jiazhong
Liu, Huanxiang
Gramatica, Paola
Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists
title Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists
title_full Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists
title_fullStr Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists
title_full_unstemmed Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists
title_short Combined Ligand/Structure-Based Virtual Screening and Molecular Dynamics Simulations of Steroidal Androgen Receptor Antagonists
title_sort combined ligand/structure-based virtual screening and molecular dynamics simulations of steroidal androgen receptor antagonists
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5331419/
https://www.ncbi.nlm.nih.gov/pubmed/28293633
http://dx.doi.org/10.1155/2017/3572394
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