期刊名称：Beni-Suef University Journal of Basic and Applied Sciences
印刷版ISSN：2314-8535
电子版ISSN：2314-8543
出版年度：2017
卷号：6
期号：3
页码：219-231
DOI：10.1016/j.bjbas.2017.04.003
语种：English
出版社：Elsevier
摘要：Abstract Exponential rise in the population around the word increased the demand of food grains/crops with limited expansion of the agricultural land. To meet the demand, generation of new herbicidal agents is of primary need for the manufacturing firm. In silico tool like QSAR is one of the regularly used in designing newer compounds along with wet experiment. Photosystem-II (PS-II) regarded as one of the major target for the herbicidal agents. With this aim in the present study a series of 1H, 1,4 benzodiazepine 2,5-dione analogues as herbicidal (PS-II inhibitors) agents were subjected to QSAR analysis using 2D PaDEL descriptors (open source). Two different splitting techniques namely, kennard stone based and k-means clustering splitting were used to divide the whole data set and GFA based on MAE criteria was used a statistical method to develop a model to investigate the physicochemical and structural requirement of potential PS-II inhibitors. All the models are statistically robust both internally and externally (Q2: 0.540–0.693, R2 pred: 0.722–0.810). The activity is mostly affected by polarizabilities, electro negativities as well as substituents at the phenyl ring. Based on the results, a library of compounds was generated using SmiLib v2.0 tool (open source) and better predicted inside applicability domain compounds were identified by applying three different applicability domain (AD) approaches. Therefore the developed public QSAR models may be helpful for the scientific community for the further research.
