【摘要】 在分子结构-生物活性关系(SAR)研究中,最困难的问题之一是结构特征的计算机化表达和提取.一种有机小分子二维结构信息数值化的方法——结构框架模型法(SFM)被提出.该方法根据所研究体系结构变化的范围来定义其分子结构框架模型,进而对体系中化合物分子结构变化的全部信息进行处理,得到结构因子矩阵.介绍了SFM 的概念和方法,以及SFM 与模式识别相结合用于高效磺酰脲类除草剂生物活性分类和预报研究的初步结果.更多还原

【Abstract】 In the researches of the Quantitative Structure-Activity Relationship,one of the difficult problems is the representation and the extraction of molecule structuralinformations.In order to solve this problem generally,authors propose a numericalrepresentation method of molecule structural factors---Structural Frame Modelmethod(SFM).First,a model for describing molecule structural factors is defined on a set ofcompounds being studied.In the set of compounds,there must be a common mole-cular backbone.From the model definitions,the factors reflecting the differencesof molecular structures can be completely extracted.Then the whole topological structure information can be transfered to a numeri-cal matrix.The activity classification results of 55 sulfonyl urea compounds for variety oftarget plants(total of 28 systems)give out 24 correct classified systems among thetotal 28 systems.The successful rate of systems is 86%.For compounds in a system,the correct rate is more than 87%.In order to check the stability and reliability of predictions of SFM method,computer tests on activity predictions are performed,using the leave-N-out approach(N=5).The average correct rate of predictions is 81%.These results show the new method is stable and reliable.更多还原