Exploring Type II Diabetes Inhibitors from Genus Daphne Plant-species: An Integrated Computational Study.

Background: Plant species of the genus Daphne clasps a historical background with a potential source of bioactive phytochemicals such as flavonoids and daphnodorins. These compounds manifest a significant chemotaxonomic value in drug discovery. Their flair comprehensive pharmacological, phytochemical, biological, catalytic, and clinical utilities make them exclusively unique. This study was conducted to investigate the optimization and structure-based virtual screening of these peculiar analogs. The majority of the active constituents of medicines are obtained from natural products. Previously, before the invention of virtual screening methods or techniques, almost 80% of drugs were obtained from natural resources. Comparing reported data to drug discovery from 1981 to 2007 signifies that half of the FDA-approved drugs are obtained from natural resources. It has been reported that structures of natural products that have particularities of structural diversity, biochemical specification, and molecular properties make them suitable products for drug discovery. These products basically have unique chiral centers which increase their structural complexity than the synthesized drugs.

Method: This work aimed to probe the use of daphnodorins analogs for the first time as antidiabetic inhibitors based on significant features and to determine the potential of daphnodorin analogs as antidiabetic inhibitors through computational analysis and structure-based virtual screening. A dataset of 38 compounds was selected from different databases, including PubChem and ZINC, for computational analysis, and optimized compounds were docked against various co-crystallized structures of inhibitors, antagonists, and receptors which were downloaded from PDB by using AutoDock Vina (by employing Broyden-Fletcher-Goldfarb-Shanno method), Discovery studio visualizer 2020, PYMOL (Schrodinger). Docking results were further validated by Molecular dynamic simulation and MM-GBSA calculation. Quantitative structure-activity relationship (QSAR) was reported by using Gaussian 09W by intimating Density Functional Theory (DFT). Using this combination of multi-approach computational strategy, 14 compounds were selected as potential exclusive lead compounds, which were analyzed through ADMET studies to pin down their druglike properties and toxicity.

Result: At significant phases of drug design approaches regular use of molecular docking has helped to promote the separation of important representatives from 38 pharmaceutically active compounds by setting a threshold docking score of -9.0 kcal/mol which was used for their exposition. Subsequently, by employing a threshold it was recognized that 14 compounds proclaimed this threshold for antidiabetic activity. Further, molecular dynamic simulation, MM-GBSA, ADMET, and DFT results screened out daphnegiralin B4 (36) as a potential lead compound for developing antidiabetic agents.

Conclusion: Our analysis took us to the conclusion that daphnegiralin B4 (36) among all ligands comes out to be a lead compound having drug-like properties among 38 ligands being non-carcinogenic and non-cytotoxic which would benefit the medical community by providing significant drugs against diabetes. Pragmatic laboratory investigations identified a new precursor to open new doors for new drug discovery.