Antiandrogens bicalutamide, flutamide and enzalutamide etc. have been used in clinical trials to treat prostate cancer by binding to and antagonizing androgen receptor (AR). Although initially effective, the drug resistance problem will emerge eventually, which results in a high medical need for novel AR antagonist exploitation. Here in this work, to facilitate the rational design of novel AR antagonists, we studied the structure-activity relationships of a series of 2-quinolinone derivatives and investigated the structural requirements for their antiandrogenic activities. Different modeling methods, including 2D MLR, 3D CoMFA and CoMSIA, were implemented to evolve QSAR models. All these models, thoroughly validated, demonstrated satisfactory results especially for the good predictive abilities. The contour maps from 3D CoMFA and CoMSIA models provide visualized explanation of key structural characteristics relevant to the antiandrogenic activities, which is summarized to a position-specific conclusion at the end. The obtained results from this research are practically useful for rational design and screening of promising chemicals with high antiandrogenic activities.

A Combined Quantitative Structure-Activity Relationship Research of Quinolinone Derivatives as Androgen Receptor Antagonists

GRAMATICA, PAOLA
2015-01-01

Abstract

Antiandrogens bicalutamide, flutamide and enzalutamide etc. have been used in clinical trials to treat prostate cancer by binding to and antagonizing androgen receptor (AR). Although initially effective, the drug resistance problem will emerge eventually, which results in a high medical need for novel AR antagonist exploitation. Here in this work, to facilitate the rational design of novel AR antagonists, we studied the structure-activity relationships of a series of 2-quinolinone derivatives and investigated the structural requirements for their antiandrogenic activities. Different modeling methods, including 2D MLR, 3D CoMFA and CoMSIA, were implemented to evolve QSAR models. All these models, thoroughly validated, demonstrated satisfactory results especially for the good predictive abilities. The contour maps from 3D CoMFA and CoMSIA models provide visualized explanation of key structural characteristics relevant to the antiandrogenic activities, which is summarized to a position-specific conclusion at the end. The obtained results from this research are practically useful for rational design and screening of promising chemicals with high antiandrogenic activities.
2015
http://www.benthamdirect.org/pages/all_b_bypublication.php
Androgen receptor (AR); Comparative molecular field analysis (CoMFA); Comparative molecular similarity indices analysis (CoMSIA); Multiple linear regression (MLR); Prostate cancer (PCa); Drug Discovery3003 Pharmaceutical Science; Computer Science Applications1707 Computer Vision and Pattern Recognition; Organic Chemistry
Wang, Yuwei; Bai, Fang; Cao, Hong; 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/11383/2030613
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