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

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(英文)

作　　者：包新华[1] 陆文聪[1] 刘亮[1] 陈念贻[1] 

机构地区：[1]上海大学理学院化学系

出　　处：《Acta Pharmacologica Sinica》2003年第5期472-476,480,共6页中国药理学报（英文版）

基　　金：Project supported by Ford-China Foundation, № 9716214.

摘　　要：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.目的:研究N-(3-氧-3,4-二氢-2H-苯并[1,4](口恶)嗪-6-羰基)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。

关 键 词：GUANIDINES structure-activity relationship sodium-hydrogen antiporter pattern recognition hyperpolyhedron models 

分 类 号：R965.1[医药卫生—药理学]