Exploring structural requirements for peripherally acting 1,5-diaryl pyrazole-containing cannabinoid 1 receptor antagonists for the treatment of obesity

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• 作者：Mayank Kumar Sharma ; Prashant R. Murumkar ; Rajani Giridhar…
• 关键词：3D ; QSAR ; Endocannabinoids ; CB1 receptor antagonists ; 1 ; 5 ; Diaryl pyrazole ; Rimonabant
• 刊名：Molecular Diversity
• 出版年：2015
• 出版时间：November 2015
• 年：2015
• 卷：19
• 期：4
• 页码：871-893
• 全文大小：3,890 KB
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• 作者单位：Mayank Kumar Sharma (1)
  Prashant R. Murumkar (1)
  Rajani Giridhar (1)
  Mange Ram Yadav (1)
  
  1. Pharmacy Department, Faculty of Technology & Engineering, Kalabhavan, The M. S. University of Baroda, Vadodara, 390 001, India
  
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Chemistry
  Analytical Chemistry
  Polymer Sciences
  Organic Chemistry
  Pharmacy
  
• 出版者：Springer Netherlands
• ISSN：1573-501X

文摘

Peripherally acting cannabinoid 1 (CB1) receptor antagonists are considered as potential therapeutics for the treatment of obesity with desired efficacy and reduced central nervous system side effects. A dataset of 72 compounds containing the 1,5-diaryl pyrazole basic skeleton having peripheral CB1 receptor antagonistic activity was utilized for three-dimensional quantitative structure–activity relationship studies. Compounds of the series exhibited high variations in the biological activity and chemical structures. Different types of molecular alignments, such as atom-based, data-based, centroid-based and centroid/atom-based were utilized to develop the best CoMFA model. The best CoMFA model was obtained with a database alignment and the same alignment was further used for the development of a CoMSIA model. The best developed CoMFA model had \(r^{2}_\mathrm{cv} = 0.552\) with six components, \(r^{2}_\mathrm{ncv} = 0.973,\,\mathrm{standard\,error\,of\,estimate} = 0.162,\,F{\text {-value}} = 281.239,\) while the best developed CoMSIA model had \(r^{2}_\mathrm{cv} = 0.571\) with six components, \(r^{2}_\mathrm{ncv} = 0.960,\, \mathrm{standard} \mathrm{error\,of\,estimate} = 0.196\) and \(F{\text {-value}} = 188.701.\) The predictive \(r^{2}\) values of these two models showed test set predictions of 0.528 and 0.679 for the best CoMFA and CoMSIA models, respectively. Based on a higher \(r^{2}_\mathrm{pred}\) value, the CoMSIA model was found to be the best one. The prediction accuracy and reliability of the best developed CoMSIA model have been validated using well-established methods. Using the inputs from the best CoMSIA contour maps, several novel highly selective peripherally acting CB1 receptor antagonists have been designed and reported herein. Keywords 3D-QSAR Endocannabinoids CB1 receptor antagonists 1, 5-Diaryl pyrazole Rimonabant