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一种用于寻找锥虫硫醇还原酶抑制剂的虚拟筛选方法。

A virtual screening approach applied to the search for trypanothione reductase inhibitors.

作者信息

Horvath D

机构信息

CEREP Lille, France.

出版信息

J Med Chem. 1997 Jul 18;40(15):2412-23. doi: 10.1021/jm9603781.

DOI:10.1021/jm9603781
PMID:9240356
Abstract

A prediction algorithm of the binding affinity of ligands to trypanothione reductase (TR), the enzyme replacing glutathione reductase in the metabolism of trypanosomatidae, has been used for the "virtual screening" of a data base of 2500 molecular sketches and has detected several structures of putative TR ligands. Most of these compounds turned out to be micromolar inhibitors of TR, as predicted by the algorithm. While their inhibitory potencies are lower than those of previously reported compounds, one of the molecules reported here could represent the lead toward a structurally different class of TR inhibitors. The fully automated prediction algorithm converts the 2D molecular sketches into 3D ligand structures, explores the conformational space of the latter, and performs a grid-based, rigid-body docking of the resulting family of ligand conformations into the TR site, calculating enthalpic and entropic binding indexes and predicting the binding affinity. The docking model has also been used to obtain hints about the binding modes of TR ligands.

摘要

一种预测配体与锥虫硫醇还原酶(TR)结合亲和力的算法已被用于对2500个分子草图数据库进行“虚拟筛选”,该酶在锥虫科的代谢中替代了谷胱甘肽还原酶,并检测到了几种假定的TR配体结构。正如该算法所预测的,这些化合物中的大多数结果证明是TR的微摩尔级抑制剂。虽然它们的抑制效力低于先前报道的化合物,但本文报道的其中一种分子可能代表了一类结构不同的TR抑制剂的先导物。这种全自动预测算法将二维分子草图转化为三维配体结构,探索后者的构象空间,并将所得的配体构象家族进行基于网格的刚体对接至TR位点,计算焓和熵结合指数并预测结合亲和力。对接模型还被用于获取有关TR配体结合模式的线索。

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