LEA3D: A computer-aided ligand design for structure-based drug design
LEA3D: A computer-aided ligand design for structure-based drug design
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DOI：
10.1021/jm0492296
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发表时间：
2005-04-07
影响因子：
7.3
通讯作者：
Pochet, S
中科院分区：
文献类型：
--
作者：
Douguet, D;Munier-Lehmann, H;Pochet, S
我们提出了 LEA 为设计有机分子而开发的程序的改进版本。合理的药物设计涉及寻找大型组合的解决方案。穷举搜索是不切实际的问题。遗传算法为研究此类问题提供了工具。名为 LEA3D 的新软件现在能够通过组合 3D 片段来构建有机分子。从生物化合物和已知药物中提取片段。适应度函数指导优化分子以获得最佳属性值的搜索过程。适应度函数是通过组合多个独立的属性评估来建立的，包括FlexX对接程序提供的分数。描述了从头药物设计中的一项应用。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天然底物之一的类似物。在 22 种测试化合物中，17 种显示出微摩尔范围内的抑制活性。
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.