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基于药效团建模、虚拟筛选和对接方法对新型CYP17抑制剂的计算预测

Computational prediction of new CYP17 inhibitors based on pharmacophore modeling, virtual screening and docking approach.

作者信息

Haidar S, Hartmann R W

出版信息

Pharmazie. 2017 Sep 1;72(9):529-536. doi: 10.1691/ph.2017.7516.

DOI:10.1691/ph.2017.7516
PMID:29441980
Abstract

17α-Hydroxylase/C17-20-lyase (P450 17, CYP 17) is an important enzyme in the androgen biosynthesis and inhibitors of this enzyme can be used for the treatment of prostate cancer. With the aim of developing new inhibitors for the target enzyme, we generated a structure-based pharmacophore model to further explain the binding requirements for human CYP17 inhibitors. Seven common features of steroidal CYP17 inhibitors were determined using MOE software. This pharmacophore model was then used to search the Cambridge Structural Database (CSD) with the aim of developing more potent and selective CYP17 inhibitors by identifying new hits. We were able to identify 36 structures as possible active CYP17 inhibitors. Docking studies for the selected compounds from the database were also performed and the best three compounds were chosen as possible hits.

摘要

17α-羟化酶/C17-20裂解酶(P450 17,CYP 17)是雄激素生物合成中的一种重要酶,该酶的抑制剂可用于治疗前列腺癌。为了开发针对该靶酶的新型抑制剂,我们构建了一个基于结构的药效团模型,以进一步阐释人CYP17抑制剂的结合要求。使用MOE软件确定了甾体类CYP17抑制剂的七个共同特征。然后,该药效团模型被用于搜索剑桥结构数据库(CSD),目的是通过识别新的命中物来开发更有效和更具选择性的CYP17抑制剂。我们能够鉴定出36种结构作为可能的活性CYP17抑制剂。还对从数据库中选择的化合物进行了对接研究,并选择了最佳的三种化合物作为可能的命中物。

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