Abstract Diabetes is a major health problem worldwide predisposing to increased mortality and morbidity. The current antidiabetic therapies have serious side effects and thus have emphasis on further need to develop effective medication therapy. Free fatty acid1 receptor (FFA1R) or G-protein-coupled receptor 40 (GPR40) represents an interesting target for developing novel antidiabetic drug. In the current study, the FFA1R agonistic activity of drug-like molecules was screened by employing pharmacophore modeling, docking, and molecular dynamics (MD) simulation. Hierarchical screening of virtual library of drug-like compounds was performed. This combined computational approach of pharmacophore mapping and structure-based approach was used to identify common hits, and the absorption, distribution, metabolism and excretion (ADME) prediction supported the analysis of their pharmacokinetic potential. MD simulation studies of the GPR40 complex with the most promising hit found in this study further validated are approached. The key residues Arg183, Arg258, Tyr91, and Tyr240 of the binding pocket were acknowledged as essential and were found to be associated in the key interactions with the most potential hit. These studies will hopefully provide scope for efficiently designing and screening new compounds as active drug candidates with more selectivity for hGPR40. To the best of our knowledge, this is the first example of the successful application of both ligand and structurebased virtual-screening techniques to discover novel GPR40 agonists. Communicated by Ramaswamy H. Sarma Graphical Abstract
Identification of novel G-protein-coupled receptor 40 (GPR40) agonists by hybrid in silico-screening techniques and molecular dynamics simulations thereof
Virendra Nath,R. Ahuja,Vipin Kumar
Published 2018 in Journal of Biomolecular Structure and Dynamics
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- Publication year
2018
- Venue
Journal of Biomolecular Structure and Dynamics
- Publication date
2018-12-07
- Fields of study
Medicine, Chemistry, Computer Science
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- Source metadata
Semantic Scholar, PubMed
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