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彭:一种基于神经气体的药效团阐释方法。LTA4H新型配体的方法设计、验证及虚拟筛选。

PENG: a neural gas-based approach for pharmacophore elucidation. method design, validation, and virtual screening for novel ligands of LTA4H.

作者信息

Moser Daniel, Wittmann Sandra K, Kramer Jan, Blöcher René, Achenbach Janosch, Pogoryelov Denys, Proschak Ewgenij

机构信息

Institute of Pharmaceutical Chemistry, Goethe University , 60438 Frankfurt, Germany.

出版信息

J Chem Inf Model. 2015 Feb 23;55(2):284-93. doi: 10.1021/ci500618u. Epub 2015 Feb 9.

Abstract

The pharmacophore concept is commonly employed in virtual screening for hit identification. A pharmacophore is generally defined as the three-dimensional arrangement of the structural and physicochemical features of a compound responsible for its affinity to a pharmacological target. Given a number of active ligands binding to a particular target in the same manner, it can reasonably be assumed that they have some shared features, a common pharmacophore. We present a growing neural gas (GNG)-based approach for the extraction of the relevant features which we called PENG (pharmacophore elucidation by neural gas). Results of retrospective validation indicate an acceptable quality of the generated models. Additionally a prospective virtual screening for leukotriene A4 hydrolase (LTA4H) inhibitors was performed. LTA4H is a bifunctional zinc metalloprotease which displays both epoxide hydrolase and aminopeptidase activity. We could show that the PENG approach is able to predict the binding mode of the ligand by X-ray crystallography. Furthermore, we identified a novel chemotype of LTA4H inhibitors.

摘要

药效团概念通常用于虚拟筛选以识别活性化合物。药效团一般被定义为化合物的结构和物理化学特征的三维排列,这些特征决定了其与药理靶点的亲和力。给定多个以相同方式与特定靶点结合的活性配体,可以合理推测它们具有一些共同特征,即一个共同的药效团。我们提出了一种基于生长神经气体(GNG)的方法来提取相关特征,我们称之为PENG(通过神经气体阐明药效团)。回顾性验证结果表明生成的模型质量可接受。此外,还对白三烯A4水解酶(LTA4H)抑制剂进行了前瞻性虚拟筛选。LTA4H是一种双功能锌金属蛋白酶,具有环氧化物水解酶和氨肽酶活性。我们能够证明PENG方法能够通过X射线晶体学预测配体的结合模式。此外,我们还鉴定出了一种新型的LTA4H抑制剂化学类型。

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