虚拟筛选
雄激素受体
前列腺癌
计算生物学
药物发现
DNA
化学
领域(数学分析)
生物
计算机科学
遗传学
生物化学
癌症
数学
数学分析
作者
Mariia Radaeva,Hélène Morin,Mohit Pandey,Fuqiang Ban,Maria Guo,Eric Leblanc,Nada Lallous,Artem Cherkasov
标识
DOI:10.1002/minf.202300026
摘要
Abstract Androgen receptor (AR) inhibition remains the primary strategy to combat the progression of prostate cancer (PC). However, all clinically used AR inhibitors target the ligand‐binding domain (LBD), which is highly susceptible to truncations through splicing or mutations that confer drug resistance. Thus, there exists an urgent need for AR inhibitors with novel modes of action. We thus launched a virtual screening of an ultra‐large chemical library to find novel inhibitors of the AR DNA‐binding domain (DBD) at two sites: protein‐DNA interface (P‐box) and dimerization site (D‐box). The compounds selected through vigorous computational filtering were then experimentally validated. We identified several novel chemotypes that effectively suppress transcriptional activity of AR and its splice variant V7. The identified compounds represent previously unexplored chemical scaffolds with a mechanism of action that evades the conventional drug resistance manifested through LBD mutations. Additionally, we describe the binding features required to inhibit AR DBD at both P‐box and D‐box target sites.
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