Identification of potential natural analgesic compounds through molecular docking-virtual screening, molecular dynamics simulation, MM/GBSA, DFT, and ADMET computations

This study aimed to identify bioactive compounds from twelve medicinal plants known for their analgesic and anti-inflammatory properties using in silico approaches. The phytochemical components were subjected to cross-docking analyses against receptors implicated in pain and inflammation pathways. Based on binding energies, interaction profiles, and key amino acid residues within the receptor active sites, three compounds-apigenin, kaempferol, and quercetin-demonstrated the highest affinity for the cyclooxygenase-2 (COX-2) receptor. Notably, these compounds share similar structural scaffolds and exhibit analogous interactions with critical receptor residues. Furthermore, pharmacokinetic and toxicity assessments of the selected compounds indicated favorable oral bioavailability and an overall acceptable safety profile. Density functional theory (DFT) calculations revealed that these compounds possess relatively high softness. Molecular dynamics simulations of apigenin, kaempferol, quercetin, and the reference drug diclofenac complexed with COX-2 were performed over 100 ns. Analyses of root mean square deviation (RMSD), radius of gyration (Rg), root mean square fluctuation (RMSF), and ligand-protein interactions confirmed the stability of these complexes. Finally, MM/GBSA calculations estimated the binding free energies, with diclofenac and apigenin exhibiting the most favorable values. This study highlights pharmacologically active compounds potentially contributing to the analgesic effects of these plants. It underscores the value of such computational investigations in accelerating the discovery of specific bioactive agents responsible for therapeutic effects.