theoretical and computational study of bioactive compounds from 𝑀𝑦𝑟𝑖𝑐𝑎 𝑛𝑎𝑔𝑖 as inhibitors of neuroendocrine and opioid receptors: a molecular docking and dynamics approach

Myrica nagi, a traditional medicinal plant, is known for its diverse phytoconstituents that exhibit neuroprotective, antidiabetic, and analgesic properties. this study utilized an integrated computational approach—molecular docking, molecular dynamics simulations, and admet profiling—to investigate the inhibitory potential of key phytochemicals against three pharmacologically significant targets: norepinephrine transporter, sulfonylurea receptor 1, and mu-opioid receptor. molecular docking analysis identified flavylium as a potent net inhibitor with the highest docking score (-7.586 kcal/mol), indicating potential antidepressant activity. myricanone showed strong binding to sulfonylurea receptor 1 (-6.982 kcal/mol), suggesting antidiabetic efficacy, whereas myricitrin exhibited the highest affinity for mu-opioid receptor (-7.398 kcal/mol), reflecting its analgesic potential. md simulations confirmed the structural stability and dynamic integrity of these complexes, with myricitrin– mu-opioid receptor demonstrating the lowest rmsd and consistent rmsf values, supporting sustained ligand-receptor interactions. moreover, admet analysis demonstrated advantageous pharmacokinetic and safety profiles of myricanone and myricitrin, including effective intestinal absorption, low toxicity, and adequate bioavailability. these compounds also demonstrate a low risk of environmental toxicity. collectively, these findings highlight the multi-target pharmacological potential of myrica nagi phytoconstituents and underscore the value of computational strategies for screening natural compounds for drug discovery. this study provides a scientific basis for the continued investigation and development of myrica nagi -derived compounds as candidates for treating neuropsychiatric, metabolic, and pain-related disorders.