Modelling the cytotoxic activity of pyrazolo-triazole hybrids using descriptors calculated from the open source tool "PaDEL-descriptor"

被引:24
作者
Amin, Sk. Abdul [1 ]
Gayen, Shovanlal [1 ]
机构
[1] Dr Hari Singh Gour Vishwavidyalaya, Dept Pharmaceut Sci, Lab Drug Design & Discovery, Sagar 470003, MP, India
关键词
Pyrazolo-triazole hybrids; Cancer; QSAR; PaDEL-Descriptor; S-MLR; K-means clustering; DRUG DISCOVERY; LEAD DISCOVERY; QSAR; ANALOGS; INHIBITORS; AGENTS;
D O I
10.1016/j.jtusci.2016.04.009
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this study, we developed QSAR models for the anti-proliferative activity of pyrazolo-triazole hybrids [(1-benzy1-1H-1,2,3triazol-4-y1)(1,3-diphenyl-1H-pyrazol-4-y1) methanone] on human brain cancer (U87MG), lung cancer (A549), prostate cancer (PC-3), and colon cancer (HT-29) cell lines. We employed K-means cluster analysis to split the data sets. Statistically robust models were generated [pIC(50) (U87MG): R= 0.873, Q(2)=0.554, R-pred(2), = 0.866; pIC(50) (A549): R= 0.879, Q(2) = 0.637, R-pred(2) = 0.858; pIC(50) (PC3): R = 0.953; Q(2)=0.850; R-pred(2) = 0.796;pIC(50) (HT-29): R = 0.962, Q(2) = 0.891; R-pred(2) = 0.707]. The reliability of these models was confirmed by acceptable validation parameters, and these models also satisfied the Golbraikh and Tropsha acceptable model criteria. The QSAR study highlighted the atomic feature and molecular descriptors, information content descriptors, and topological and constitutional descriptors that affect anti-cancer activity. (C) 2016 The Authors. Production and hosting by Elsevier B.V.
引用
收藏
页码:896 / 905
页数:10
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