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LEA3D:一种用于基于结构的药物设计的计算机辅助配体设计。

LEA3D: a computer-aided ligand design for structure-based drug design.

作者信息

Douguet Dominique, Munier-Lehmann Hélène, Labesse Gilles, Pochet Sylvie

机构信息

Centre de Biochimie Structurale (CNRS UMR 5048, INSERM UMR U554), Faculté de Pharmacie, Université Montpellier I, 15, avenue Charles Flahault, 34060 Montpellier Cedex, France.

出版信息

J Med Chem. 2005 Apr 7;48(7):2457-68. doi: 10.1021/jm0492296.

Abstract

We present an improved version of the program LEA developed to design organic molecules. Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a tool for the investigation of such problems. New software, called LEA3D, is now able to conceive organic molecules by combining 3D fragments. Fragments were extracted from both biological compounds and known drugs. A fitness function guides the search process in optimizing the molecules toward an optimal value of the properties. The fitness function is build up by combining several independent property evaluations, including the score provided by the FlexX docking program. One application in de novo drug design is described. The example makes use of the structure of Mycobacterium tuberculosis thymidine monophosphate kinase to generate analogues of one of its natural substrates. Among 22 tested compounds, 17 show inhibitory activity in the micromolar range.

摘要

我们展示了为设计有机分子而开发的程序LEA的改进版本。合理药物设计涉及解决大型组合问题,而穷举搜索对此并不实用。遗传算法为研究此类问题提供了一种工具。名为LEA3D的新软件现在能够通过组合3D片段来构思有机分子。片段既从生物化合物中提取,也从已知药物中提取。一个适应度函数在将分子优化至属性的最优值的过程中引导搜索进程。该适应度函数通过组合几个独立的属性评估构建而成,包括FlexX对接程序提供的分数。文中描述了在从头药物设计中的一个应用。该示例利用结核分枝杆菌胸苷单磷酸激酶的结构来生成其一种天然底物的类似物。在22种测试化合物中,有17种在微摩尔范围内显示出抑制活性。

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