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一种常见的基于特征的 3D 药效团模型生成和虚拟筛选:鉴定潜在的 PfDHFR 抑制剂。

A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors.

机构信息

National Institute of Pharmacuetical Education and Research, S.A.S. Nagar, Mohali, India.

出版信息

J Enzyme Inhib Med Chem. 2010 Oct;25(5):635-45. doi: 10.3109/14756360903393817.

Abstract

A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors.

摘要

从一组 24 种化合物中构建了一个具有四个特征的 3D 药效团模型,这些化合物的活性针对恶性疟原虫二氢叶酸还原酶(PfDHFR)的 V1/S 株进行了报道。该酶带有 Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu 突变。使用 Catalyst 程序的 HipHop 模块生成了该模型。根据训练集化合物在特定假设上的排列或最佳拟合值,从 HipHop 生成的 10 个假设中选择最佳模型。最佳模型(hypo1)由两个氢键供体、一个疏水芳基和一个疏水脂肪族特征组成。Hypo1 被用作查询,对 Maybridge2004 和 NCI2000 数据库进行虚拟筛选。从搜索中获得的命中随后进行 FlexX 和 Glide 对接研究。基于四重突变 PfDHFR 活性部位的结合评分和相互作用,确定了一组 9 种命中物为潜在抑制剂。

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