Virtual screening of metabolites from mulberry (Morus alba L.) leaves as anti-hyperglycemic agents through molecular docking against multiple targets

Background: Mulberry (Morus alba L.) leaves have been widely studied as an anti-hyperglycemic agent. However, the mechanism of action and metabolites responsible for their anti-hyperglycemic activity are not yet known. Objective: This research aims to virtually screen active compounds from mulberry leaves using the molecular docking method against multi-targets related to hyperglycemia activity. Method: A total of 157 metabolites from mulberry leaves were made into 10 conformers and docked by using PLANTS against 12 different targets. Three best compounds for each target were then filtered, analyzed based on Lipinski’s rule of five, and plotted into a BOILED-Egg diagram to analyze their oral bioavailability. Result: Sixteen compounds dominated the top ranking of docking scores against 12 different targets. Sanggenol M is one of the most promising compounds that are capable of scoring a high ranker in 7 different targets: α-glucosidase, dipeptidyl peptidase-4, free fatty acid receptors-1, glycogen phosphorylase, glucagon receptor, ATP-sensitive potassium channel, and AMP-activated protein kinase. However, Lipinski’s rule of five and BOILED-Egg diagram analysis predicted that Sanggenol M has poor oral bioavailability. Conclusion: Sanggenol M has a good potential to be developed into an antihyperglycemic agent and further development needs to be done to increase its oral bioavailability.