超多面体模型用于Na／H交换抑制剂胍类化合物的分子筛选

目的：研究N-(3—氧—3,4—二氢—2H-苯并[1,4]噁嗪—6—碳基)胍类化合物的量子化学结构参数与Na／H交换抑制活性的关系,探讨计算机辅助识别该类化合物生物活性的手段．方法：用我们独创的超多面体模型．结果：用超多面体模型总结出该类化合物(样本)在多维空间中的分布区域,建立了该类化合物的构效关系．并用“留一法”比较了PCA、Fisher方法与超多面体模型的预报能力．结论：对同一套数据的胍类化合物分子,用超多面体模型作分子筛选的准确率比用PCA和Fisher方法高．因此,超多面体模型可望成为筛选新高活性化合物的一个有力工具．

Hyper-polyhedron model applied to molecular screening of guanidines as Na/H exchange inhibitors

AIM: To investigate structure-activity relationships of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines in Na/H exchange inhibitory activities and probe into a new method of the computer-aided molecular screening. METHODS: The hyper-polyhedron model(HPM) was proposed in our lab. RESULTS: The samples with probably higher activities could be determined in such a way that their representing points should be in the hyper-polyhedron region where all known samples with high activities were distributed. And the predictive ability of different methods available was tested by the cross-validation experiment. CONCLUTION: The accurate rate of molecular screening of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines by HPM was much higher than that obtained by PCA (principal component analysis) and Fisher methods for the data set available here. Therefore, HPM could be used as a powerful tool for screening new compounds with probably higher activities.