Mechanistic insights into antidiabetic potential of Ficus viren against multi organ specific diabetic targets: molecular docking, MDS, MM-GBSA analysis
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引用次数: 0
Abstract
Ficus viren has been traditionally used to treat diabetes, and its extract inhibits carbohydrate/lipid metabolism and possesses anti-hyperglycemic potential. However, there is conflicting investigation related to F. viren extract effect on carbohydrate metabolism. Thus, bioactive and mechanism behind its antidiabetic potential is still scanty. This study explored F. viren’s anti-diabetic property by identifying potential phytoconstituents and mechanism. A sequential in-silico approach was used i.e., druglikeness, molecular docking, post-docking MM-GBSA, ADMET studies, molecular dynamic simulation (MDS), and post-MDS MM-GBSA. We screened ∼32 phytoconstituents and twelve potential organ-specific diabetic targets (O.S.D.Ts i.e., IR, DPP-4, ppar-γ, ppar-α, ppar-δ, GLP-1R, SIRT-1, AMPK, GSK-3β, RAGE, and AR). Drug likeness study identified 18 druggable candidates among 32 phytoconstituents. K3A, quercetin, scutellarein, sorbifolin, and vogeline J identified as potential ligands from druggable ligands, using IR as the standard target. Subsequently, potential ligands docked with remaining O.S.D.Ts. and data showed that K3A binds strongly with AMPK, ppar-δ, DPP-4, and GSK-3β, while scutellarein binds with AR and ppar-α. Sorbifolin, quercetin, and vogeline J binds with ppar-α, ppar-γ, and RAGE, respectively. Post-docking MM-GBSA data (∆GBind) also depicted potential ligand’s strong binding affinities with their corresponding targets. Thereafter, simulation data revealed that only scutellarein and sorbifolin showed dynamic stability with their respective targets, i.e., AR/ppar-α and ppar-α, respectively. Interestingly, post-MDS MM-GBSA revealed that only scutellarein exhibited strong ∆GBind of −55.08 kcal/mol and −75.48 kcal/mol with AR and ppar-α, respectively. Though, collective computational analysis supports antidiabetic potential of F. viren through AR and ppar-α modulation by scutellarein.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
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