Network pharmacology and molecular docking-based approach to predict the molecular targets and mechanisms of action of Melissa officinalis in Type-2 diabetes mellitus

Network pharmacology, molecular docking, and molecular dynamics (MD) studies were used to investigate the molecular targets and mechanisms of action of Melissa officinalis phytoconstituents in type-2 diabetes mellitus (T2DM). SciFinder was used to retrieve previously known phytoconstituents from M. officinalis aerial parts. Targets related to these compounds were predicted using the Swiss TargetPrediction, SEA (similarity ensemble approach) and BindingDB databases, and were intersected with T2DM-relevant targets from public databases. Networks were constructed using the STRING online tool and Cytoscape (v.3.9.1) software. Gene ontology/KEGG pathway analysis was performed using DAVID and SHINEGO 0.77. Molecular docking used the MOE suite. MD simulations were conducted for 100 ns using GROMACS 2023 with a CHARMM36 force field. A total of 17 phytoconstituents and 154 targets associated with T2DM were identified. The protein–protein interaction (PPI) and target–pathway (TP) network analysis identified key hub genes, including EGFR, SRC, AKT1, TNF, PPARG, PIK3R1, RELA, INSR, GSK3B, PIK3CG, FYN, PTBIN, and PPARA, with critical roles in insulin resistance and T2DM-relevant pathways. The pathway enrichment analysis highlighted notable involvement in insulin signaling, inflammation, and diabetic complications. The compound–target (CT) network predicted quercetin, luteolin, ursolic acid, isoquercitrin, 2α-hydroxy-ursolic acid, and oleanolic acid to be key bioactive compounds. Molecular docking, followed by MD studies, identified that isoquercitrin showed most energetically favorable and stable complexes with three targets, namely EGFR, PPARα, and AKT1. These findings enhance our understanding of the antidiabetic potential of M. officinalis and underscore the need for further studies on its phytoconstituents, such as isoquercitrin, in search for new antidiabetic agents.