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基于药效团的 Hsp90 抑制剂虚拟筛选和对接研究。

Pharmacophore-based virtual screening and docking studies on Hsp90 inhibitors.

机构信息

Medicinal and Process Chemistry Division, Central Drug Research Institute, Lucknow, India.

出版信息

SAR QSAR Environ Res. 2010 Jul;21(5-6):445-62. doi: 10.1080/1062936X.2010.501817.

DOI:10.1080/1062936X.2010.501817
PMID:20818581
Abstract

Hsp90 (Heat shock protein 90) is an important therapeutic target for the treatment of cancer. To identify important chemical features for Hsp90 inhibitory activity, a 3D-QSAR pharmacophore model was developed using a set of 61 inhibitors (a training set of 31 and a test set of 30 compounds) belonging to a series of 2-amino-6-halopurine and 7'-substituted benzothiazolothio- and pyridinothiazolothio-purines. The best HypoGen model consisted of five pharmacophoric features: one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) and three hydrophobic (HY) groups. It showed a high correlation coefficient (r = 0.943) and low root mean square deviation (RMSD = 0.751). This model was validated against 30 known Hsp90 inhibitors, where it showed a high predictive value for R(2)pred = 0.805], thus confirming that HY, HBA and HBD features are essential for Hsp90 inhibition. The validated pharmacophore model (Hypo-1) was used as a 3D query for virtual screening to retrieve potential inhibitors from the Maybridge and National Cancer Institute (NCI) databases. The hit compounds were subsequently subjected to molecular docking studies and, finally, five hits were prioritized as potential leads based on GoldScore function.

摘要

热休克蛋白 90(Hsp90)是治疗癌症的重要治疗靶点。为了确定 Hsp90 抑制活性的重要化学特征,使用属于一系列 2-氨基-6-卤嘌呤和 7′-取代苯并噻唑硫代和吡啶并噻唑硫代嘌呤的 61 种抑制剂(训练集 31 种和测试集 30 种化合物)建立了 3D-QSAR 药效团模型。HypoGen 模型最好的由五个药效特征组成:一个氢键受体(HBA),一个氢键供体(HBD)和三个疏水性(HY)基团。它表现出高相关系数(r = 0.943)和低均方根偏差(RMSD = 0.751)。该模型经过 30 种已知 Hsp90 抑制剂的验证,其中 R(2)pred 值为 0.805,表明 HY、HBA 和 HBD 特征对于 Hsp90 抑制是必不可少的。验证后的药效团模型(Hypo-1)被用作虚拟筛选的 3D 查询,从 Maybridge 和国家癌症研究所(NCI)数据库中检索潜在抑制剂。随后对命中化合物进行分子对接研究,最后根据 GoldScore 函数将 5 个命中化合物优先作为潜在先导化合物。

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