Zheng W, Cho S J, Tropsha A
Laboratory for Molecular Modeling, School of Pharmacy, University of North Carolina, Chapel Hill 27599-7360, USA.
J Chem Inf Comput Sci. 1998 Mar-Apr;38(2):251-8. doi: 10.1021/ci970095x.
We describe a new computational approach, called Focus-2D, to the rational design of targeted combinatorial chemical libraries. This approach is based on the hypothesis that structurally similar compounds display similar biological activity profiles. Building blocks that are used in a combinatorial chemical synthesis are randomly assembled to produce virtual library compounds. Individual library compounds are represented by Kier-Hall topological descriptors. Molecular similarities between compounds are evaluated quantitatively by modified pairwise Euclidean distances in multidimensional descriptor space. Simulated annealing is used to search the potentially large structural space of virtual chemical libraries to identify compounds similar to lead molecules. Frequency analysis of building block composition of selected virtual compounds identifies building blocks that can be used in combinatorial synthesis of chemical libraries with high similarity to the lead molecules. We show that this method correctly identifies building found in active peptoids with adrenergic or opioid activities.
我们描述了一种名为Focus-2D的新计算方法,用于靶向组合化学文库的合理设计。该方法基于这样的假设:结构相似的化合物具有相似的生物活性谱。组合化学合成中使用的构建模块被随机组装以生成虚拟文库化合物。单个文库化合物由基尔-霍尔拓扑描述符表示。通过多维描述符空间中修改后的成对欧几里得距离定量评估化合物之间的分子相似性。使用模拟退火搜索虚拟化学文库潜在的大结构空间,以识别与先导分子相似的化合物。对所选虚拟化合物的构建模块组成进行频率分析,可识别可用于组合合成与先导分子高度相似的化学文库的构建模块。我们表明,该方法能正确识别出具有肾上腺素能或阿片样活性的活性拟肽中发现的构建模块。