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| Content Provider | Springer Nature Link |
|---|---|
| Author | Sharma, Mayank Kumar Murumkar, Prashant R. Giridhar, Rajani Yadav, Mange Ram |
| Copyright Year | 2015 |
| Abstract | 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. |
| Starting Page | 871 |
| Ending Page | 893 |
| Page Count | 23 |
| File Format | |
| ISSN | 13811991 |
| Journal | Molecular Diversity |
| Volume Number | 19 |
| Issue Number | 4 |
| e-ISSN | 1573501X |
| Language | English |
| Publisher | Springer International Publishing |
| Publisher Date | 2015-07-17 |
| Publisher Place | Cham |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | 3D-QSAR Endocannabinoids CB1 receptor antagonists 1, 5-Diaryl pyrazole Rimonabant Biochemistry Organic Chemistry Polymer Sciences Pharmacy |
| Content Type | Text |
| Resource Type | Article |
| Subject | Organic Chemistry Medicine Drug Discovery Molecular Biology Physical and Theoretical Chemistry Information Systems Catalysis Inorganic Chemistry |
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