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.

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

GRAMATICA, PAOLA
2017-01-01

Abstract

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.
2017
http://www.hindawi.com/journals/biomed/
Algorithms; Androgen Receptor Antagonists; Computational Biology; Dihydrotestosterone; Drug Resistance, Neoplasm; Humans; Inhibitory Concentration 50; Ligands; Linear Models; Male; Molecular Docking Simulation; Molecular Dynamics Simulation; Molecular Structure; Prostate; Protein Binding; Quantitative Structure-Activity Relationship; Receptors, Androgen; Steroids; Thermodynamics; Immunology and Microbiology (all); Biochemistry, Genetics and Molecular Biology (all)
Wang, Yuwei; Han, Rui; Zhang, Huimin; Liu, Hongli; Li, Jiazhong; Liu, Huanxiang; Gramatica, Paola
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2061410
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