## 4 Discussion
### Limitations and Future Directions  
While the in silico molecular docking approach provides valuable initial insights into potential ligand-enzyme interactions, it is essential to acknowledge its inherent limitations [67; 68]. It is acknowledged that the rigid-body docking protocol does not account for receptor flexibility, which may influence binding site accessibility and interaction patterns. However, this approach enables the high-throughput comparison of ligand affinities and allows for the initial identification of compounds with the potential to modulate enzyme function. Future work may incorporate molecular dynamics simulations to refine the binding hypotheses and explore induced-fit effects [69].  
Furthermore, complex factors such as solvent effects, entropic contributions to binding, and the precise ionization states of catalytic residues in a physiological environment are not fully captured by current docking algorithms [70]. These limitations necessitate caution when extrapolating purely in silico findings to actual biological activity.  
The \"Match\" criterion in Table 6, while indicative, should also be interpreted with care. The definition of \"active site\" residues can vary slightly between studies, and a ligand might inhibit an enzyme by interacting with residues adjacent to or within the binding pocket, even if they are not traditionally listed as \"catalytic.\" Thus, a \"No match\" does not definitively rule out inhibitory potential, especially given the favorable binding energies and Ki values.  
To overcome the limitations of the present in silico approach and to validate the promising docking results, several follow-up studies are strongly recommended. One important step is the application of flexible-body docking, which allows for conformational changes in both the ligand and the protein. This is particularly relevant when investigating small molecules like terpenes that may induce subtle but significant shifts in the active site upon binding.  
Another essential method is the use of molecular dynamics (MD) simulations. MD can provide a time-resolved view of ligand-protein interactions, allowing for the assessment of complex stability and conformational flexibility and the estimation of binding free energies using approaches such as MM/PBSA or MM/GBSA. This offers a more nuanced and accurate prediction of binding affinity beyond static docking results.  
Beyond computational methods, experimental validation is crucial. In vitro enzymatic assays, such as those using recombinant COX or 5-LOX enzymes, can confirm inhibitory activity and enable the determination of IC\({}_{50}\) values for the most promising terpene candidates.  
Additionally, cell-based assays should be employed to assess anti-inflammatory activity in relevant biological systems, helping to bridge the gap between enzyme inhibition and biological effect. Finally, in vivo studies in animal models of inflammation are necessary to evaluate both the therapeutic potential and the safety profile of the selected terpenes, laying the groundwork for possible clinical development.  
Despite these limitations, rigid-body docking remains a cost-effective and rapid method to prioritize ligands for further experimental validation. Its application in early-phase screening helps narrow down candidates for more resource-intensive dynamic modeling and biochemical testing.  
Ultimately, this study serves as a strong foundation, identifying specific terpenes (menthol, camphor, limonene, \(\alpha\)-pinene, \(\beta\)-pinene, and linalool) with varying degrees of potential to modulate arachidonic acid metabolism through interactions with the key inflammatory enzymes. The observed structure-activity relationships, particularly the direct engagement with catalytic residues for some terpen, underscore their potential as novel anti-inflammatory agents.