## 3 Result and Discussion
### Modeling the Structures of a-Glucosidase Complexes with Main Essential Oil Compounds  
Based on the GC-MS results, the two compounds with the highest percentage in the essential oil composition of C. _operculatus_ leaves were selected for interaction analysis with \(\alpha\)-glucosidase. Two compounds, (\(Z\))-\(\beta\)-ocimene and allo-ocimene, were docked at the active site between acarbose and \(\alpha\)-glucosidase. The docking conformations of the two compounds were shown in Table 2 and Figures 1 and 2. Allo-ocimene had docking score of \(-\)5.358 kcal/mol and was found to interact with the enzyme, with six hydrophobic interactions at Trp376, Phe649, His674, Trp613, Trp516, and Ile441 (Figure 2A). Meanwhile, the results revealed (\(Z\))-\(\beta\)-ocimene had docking score of \(-\)5.330 kcal/mol, with seven Alkyl and Pi-Alkyl interactions at Phe649, Trp376, Leu405, His674, Ile441, Trp481, and Trp516 (Figure 2B). For further analysis, the best conformation of two candidates was selected for molecular dynamic simulation over 100 ns. Small molecules that interact with protein surfaces have the potential to induce significant changes in the protein's tertiary structure, thereby offering opportunities for improving drug design. Molecular dynamics modeling stands out for its capability to assess the flexibility of protein-ligand complexes. This approach was employed to precisely evaluate the thermodynamics and kinetics of drug-enzyme interactions. To assess the stability of the ligands and protein, 100 ns trajectories of the complex formed between two primary compounds and \(\alpha\)-glucosidase were analyzed. The simulation results reveal that the complex involving allo-ocimene and \(\alpha\)-glucosidase remained stable throughout the simulation, with fluctuations within a range of 2 A (Figure 3A). Furthermore, analysis of the root mean square fluctuation (RMSF) indicated that the ligand stabilized specific interacting residues at the active site (Figure 3B). The radius of gyration (Rg), which characterizes the distribution of atoms around the protein's axis, was also examined (Figure 3C). Additionally, the solvent-accessible surface area (SASA) (Figure 3D) aided in visualizing conformational changes in the protein following ligand binding. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Compound** & **Docking Score (kcal/mol)** & **Residues Interaction** \\ \hline allo-ocimene & \(-\)5.358 & Trp376, Phe649, His674, Trp613, Trp516, and Ile441 \\ (\(Z\))-\(\beta\)-ocimene & \(-\)5.330 & Phe649, Trp376, Leu405, His674, Ile441, Trp481, and Trp516 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Molecular docking results of two main essential oil compounds with \(\alpha\)-glucosidase. Meanwhile, the complex between (\(Z\))-\(\beta\)-ocimene and \(\alpha\)-glucosidase also remained stable throughout the simulation time, with fluctuations within the range of 2 A (Figure 4A). The RMSF, radius of gyration (Rg), and solvent-accessible surface area (SASA) results also demonstrated a similar interaction between allo-ocimene and \(\alpha\)-glucosidase (Figure 4B-D). This can be explained by the similar structures of the two compounds. Interestingly, there are no hydrogen bonds created from compounds and protein; however, the complexes  
Figure 3: Dynamic simulation between allo-ocimene and \(\alpha\)-glucosidase for 100 ns. (**A**) RMSD. (**B**) RMSF. (**C**) Radius of gyration. (**D**) SASA. Figure 2: (**A**) The interaction between allo-ocimene and protein. (**B**) The interaction between (\(Z\))-\(\beta\)-ocimene and protein. were quite stable because of hydrophobic interactions between double-bonds and amino acids. Although the effects of the constituents in _C. operculatus_ essential oil are believed to be synergistic in terms of \(\alpha\)-glucosidase activity, we would expect that the two main components (comprising approximately 70%) are believed to have the most impact on the \(\alpha\)-glucosidase activity of essential oils.