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CISOC-PSCT: A PREDICTIVE SYSTEM FOR CARCINOGENIC TOXICITY

机译:CISCO-PBCT:致癌毒性的预测系统

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A SAR based carcinogenic toxicity prediction system, CISOC-PSCT, was developed It consisted of two principal phases: the construction of relationships between structural descriptors and carcinogenic toxicity indices, and prediction of the toxicity from the SAR model. The training set included 2738 carcinogenic and 4130 non-carcinogenic compounds. Three predefined topological types of substructures termed Star, Path and Ring were used to generate the descriptors for each structure in the training set. In this system, the defined carcinogenic toxicity index (CTI) was obtained from the probability of a structural descriptor to either belong to the carcinogenic or non-carcinogenic compounds. Based on these structural descriptors and their CTI, a SAR model was derived. Then the carcinogenic possibility (CP) and the carcinogenic impossibility (CIP) of compounds were predicted. The model was tested from a testing set of 304 carcinogenic compounds (MDL toxicity database), 460 non-carcinogenic compounds (CMC database) and 94 compounds extracted from two traditional Chinese medicine herbs.
机译:开发了基于SAR的致癌毒性预测系统CISOC-PSCT,该系统包括两个主要阶段:构建结构描述符与致癌毒性指标之间的关系,以及根据SAR模型预测毒性。培训内容包括2738种致癌化合物和4130种非致癌化合物。使用三个预定义的拓扑类型的子结构(称为星,路径和环)来生成训练集中每个结构的描述符。在该系统中,从结构描述符属于致癌或非致癌化合物的可能性中获得了确定的致癌毒性指数(CTI)。基于这些结构描述符及其CTI,得出了SAR模型。然后预测了化合物的致癌可能性(CP)和致癌可能性(CIP)。该模型是从304种致癌化合物(MDL毒性数据库),460种非致癌化合物(CMC数据库)和从两种中药提取的94种化合物的测试集中进行测试的。

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