Purpose <p>Dengue virus (DENV), which belongs to the Flaviviridae family, remains a global health challenge due to its high morbidity and mortality rates. However, existing vaccines have limitations in availability and implementation, highlighting the urgent need for effective antiviral treatments. In this study, we utilized a comprehensive computational approach to identify potential inhibitors derived from natural products that target two crucial viral enzymes involved in DENV replication: the NS2B/NS3 protease and RNA-dependent RNA polymerase (RdRp).</p> Method <p>We used high-throughput virtual screening, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations, along with advanced analyses such as radius of gyration (RoG) and principal component analysis (PCA), to assess the stability, binding affinity, and dynamic behavior of protein-ligand complexes. Additionally, we performed pharmacokinetic and toxicity profiling to ensure the drug-likeness and safety of the selected compounds.</p> Result <p>The four lead compounds were identified, such as CNP0096663, CNP0419875, CNP0243663, and CNP0197840. Among these, CNP0419875 and CNP0243663 showed superior binding affinities and stability compared to the reference inhibitors. These compounds showed strong interactions with key residues in the active site and demonstrated stable dynamics during 500 ns molecular dynamics (MD) simulations. Additionally, these compounds exhibited favourable Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles, including high gastrointestinal absorption, metabolic stability, and minimal toxicity risks. These findings support previous studies and highlight the potential of computational approaches in antiviral drug discovery.</p> Conclusion <p>This research highlights the potential of natural product-derived inhibitors as effective therapeutic options for combating DENV.</p>