ArticleOncotarget2017
Molecular docking, 3D-QSAR and structural optimization on imidazo-pyridine derivatives dually targeting AT1 and PPARg.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 7 citations in OpenAlex.
- Fatty acid amide hydrolase inhibition and N-arachidonoylethanolamine modulation by isoflavonoids: A novel target for upcoming antidepressants.Pharmacology research & perspectives · 2022Article
- Kaempferol Facilitated Extinction Learning in Contextual Fear Conditioned Rats via Inhibition of Fatty-Acid Amide Hydrolase.Molecules (Basel, Switzerland) · 2020Article
- Computer-aided design of temozolomide derivatives based on alkylglycerone phosphate synthase structure with isothiocyanate and their pharmacokinetic/toxicity prediction and anti-tumor activityBiomedical reports · 2018Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
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Abstract
Telmisartan, a bifunctional agent of blood pressure lowering and glycemia reduction, was previously reported to antagonize angiotensin II type 1 (AT1) receptor and partially activate peroxisome proliferator-activated receptor γ (PPARγ) simultaneously. Through the modification to telmisartan, researchers designed and obtained imidazo-\pyridine derivatives with the IC50s of 0.49~94.1 nM against AT1 and EC50s of 20~3640 nM towards PPARγ partial activation. For minutely inquiring the interaction modes with the relevant receptor and analyzing the structure-activity relationships, molecular docking and 3D-QSAR (Quantitative structure-activity relationships) analysis of these imidazo-\pyridines on dual targets were conducted in this work. Docking approaches of these derivatives with both receptors provided explicit interaction behaviors and excellent matching degree with the binding pockets. The best CoMFA (Comparative Molecular Field Analysis) models exhibited predictive results of q2=0.553, r2=0.954, SEE=0.127, r2pred=0.779 for AT1 and q2=0.503, r2=1.00, SEE=0.019, r2pred=0.604 for PPARγ, respectively. The contour maps from the optimal model showed detailed information of structural features (steric and electrostatic fields) towards the biological activity. Combining the bioisosterism with the valuable information from above studies, we designed six molecules with better predicted activities towards AT1 and PPARγ partial activation. Overall, these results could be useful for designing potential dual AT1 antagonists and partial PPARγ agonists.
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