prediction of the possible antidiabetic and anti-inflammatory targets of -derived phytochemicals and mechanistic insights by molecular dynamics simulations.

is used traditionally for the treatment of diabetes and its complications. However, the mode of action and the likely bioactive phytochemicals involved are not yet fully explored. GC-MS analysis was employed to identify the inherent compounds in leaves. To gain an insight into the antidiabetic mode of action of this plant, the identified phytochemicals were subjected to computational studies against four molecular targets of diabetes, dipeptidyl peptidase-4, glycogen synthase kinase 3, NADPH oxidase (NOX), sodium-glucose co-transporter-2, and one target of inflammation, cyclooxygenase-2. Compounds with notable binding affinity were subjected to druggability test. Results from molecular docking showed that seven of the compounds investigated exhibited druggability properties and had outstanding binding affinity values for these targets relative to values obtained for the respective standards of each of the targets. Analysis of the MD trajectories from a 100 ns atomistic run shows that the integrities of the complex systems were more stable and preserved throughout the simulation than the unbound protein. These results indicated that the antidiabetic and anti-inflammatory effects of these compounds might be via the inhibition of these targets, laying the foundation for further studies, such as and studies to fully validate the anti-diabetic agents from this plant.Communicated by Ramaswamy H. Sarma.