Molecular Docking Analysis of Major Bioactive Compounds from the Traditional Lom Pakang Formulation Against Cyclooxygenase-2 (COX-2)

Abstract

Lom Pakang is a disorder recognized in Thai Traditional Medicine (TTM) and has traditionally been treated using a herbal formulation consisting of black pepper (Piper nigrum L.), fresh ginger (Zingiber officinale Roscoe), kaffir lime peel (Citrus hystrix DC.), Bermuda grass (Cynodon dactylon (L.) Pers.), and calcined alum. Although this formulation has long been used to relieve inflammatory symptoms, its molecular mechanism of action remains unclear. This study aimed to investigate the molecular interactions between major bioactive compounds from the traditional Lom Pakang formulation and cyclooxygenase-2 (COX-2) using molecular docking analysis. Eight major phytochemicals, namely piperine, piperettine, 6-gingerol, 6-shogaol, citronellal, limonene, apigenin, and luteolin, were selected based on previous phytochemical studies. Three-dimensional ligand structures were obtained from the PubChem database, whereas the crystal structure of COX-2 (PDB ID: 1CX2) was retrieved from the Protein Data Bank. Molecular docking was performed using ArgusLab 4.0.1, and ligand–protein interactions were analyzed using Discovery Studio Visualizer. All investigated compounds were successfully docked within the predicted binding pocket of COX-2. Among the tested compounds, 6-shogaol exhibited the lowest predicted binding energy (−12.70 kcal/mol), followed by piperettine (−11.30 kcal/mol) and 6-gingerol (−10.98 kcal/mol). Interaction analysis indicated that 6-shogaol formed hydrogen bonds with ALA527 and SER530 together with multiple hydrophobic interactions that may contribute to stabilization of the ligand–protein complex. These findings suggest that several bioactive compounds in the traditional Lom Pakang formulation, particularly 6-shogaol, possess favorable predicted interactions with the COX-2 active site and provide preliminary computational evidence supporting the anti-inflammatory potential of the formulation. Nevertheless, further experimental studies are required to validate these computational predictions.