In the clinical treatment of prostate cancer, mutation in the androgen receptor (AR) that occurred in patients, often results in drug resistance because the agonist activity of the drug increases while the antagonist activity decreases. Recently a novel series of diazacycloundecane AR antagonists were reported, and their abilities to antagonize the wild type (WT) AR as well as antagonize the mutated type (MT) AR (T877A) were determined experimentally. In this paper, to understand more about the drug resistance and to help to design more active antagonists, the quantitative structure–activity relationship (QSAR) of these compounds were analyzed, and the different interactions of these antagonists with two types of AR were compared. As a result two robust and predictive QSAR models were proposed, and the different structure features related with the antagonist activities on WT and MT AR were analyzed separately.

Quantitative Structure-Activity Relationship Analysis of a Novel Series of Chemicals Antagonizing WT and MT AR

GRAMATICA, PAOLA
2011-01-01

Abstract

In the clinical treatment of prostate cancer, mutation in the androgen receptor (AR) that occurred in patients, often results in drug resistance because the agonist activity of the drug increases while the antagonist activity decreases. Recently a novel series of diazacycloundecane AR antagonists were reported, and their abilities to antagonize the wild type (WT) AR as well as antagonize the mutated type (MT) AR (T877A) were determined experimentally. In this paper, to understand more about the drug resistance and to help to design more active antagonists, the quantitative structure–activity relationship (QSAR) of these compounds were analyzed, and the different interactions of these antagonists with two types of AR were compared. As a result two robust and predictive QSAR models were proposed, and the different structure features related with the antagonist activities on WT and MT AR were analyzed separately.
2011
Prostate cancer Drug resistance WT AR MT AR Antagonist QSAR
Huo, X.; Li, J.; Gramatica, Paola
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/1727779
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