Virtual Screening and In Silico Simulation Analysis for Rapid and Efficient Identification of Novel Natural GPR40 Agonist

Background: Diabetes is the foremost health problem worldwide predisposing to increased mortality and morbidity. The available synthetic drugs have serious side effects and thus, emphasize further need to develop effective medication therapy. GPR40 represents an interesting target for developing novel antidiabetic drug. In the current study, searching of potential natural hit candidate as agonist by using structure based computational approach. Methods: The GPR40 agonistic activity of natural compounds was searched by using Maestro through docking and Molecular Dynamics (MD) simulation application. Virtual screening by using IBScreen library of natural compounds was done and the binding modes of newer natural entity(s) were investigated. Further, MD studies of the GPR40 complex with the most promising hit found in this study justified the stability of these complexes. Results: The silicone chip-based approach recognized the most capable six hits and the ADME prediction aided the exploration of their pharmacokinetic potential. In this study, the obtained hit (ZINC70692253) after the use of exhaustive screening having binding energy -107.501 kcal/mol and root mean square deviation of hGPR40-ZINC70692253 is around 3.5 Å in 20 ns of simulation. Conclusion: Successful application of structure-based computational screening gave a novel candidate from Natural Product library for diabetes treatment. So, Natural compounds may tend to cure diabetes with lesser extent of undesirable effects in comparison to synthetic compounds and these novel screened compounds may show a plausible biological response in the hit to lead finding of drug development process. To the best of our knowledge, this is the first example of the successful application of SBVS to discover novel natural hit compounds using hGPR40.