Open AccessDesign and combinatorial library generation of 1H 1,4 benzodiazepine 2,5 diones as photosystem-II inhibitors: A public QSAR approach
Author(s) -
Purusottam Banjare,
Jagadish Singh,
Partha Pratim Roy
Publication year - 2017
Publication title -
beni-seuf university journal of basic and applied sciences /beni-suef university journal of basic and applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2314-8543
pISSN - 2314-8535
DOI - 10.1016/j.bjbas.2017.04.003
Subject(s) - quantitative structure–activity relationship , photosystem ii , in silico , chemistry , population , rational design , applicability domain , domain (mathematical analysis) , public domain , computer science , combinatorial chemistry , stereochemistry , biological system , mathematics , nanotechnology , biology , photosynthesis , materials science , biochemistry , mathematical analysis , demography , theology , philosophy , sociology , gene
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, R2pred: 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