Dengue fever cases are spiking over the last two decades. Incessant efforts are still being made to gain deeper insights on this arboviral disease and to identify bioactive antivirals. In this study, bioinformatics analysis was conducted to identify the differentially expressed genes (DEGs) in the expression profiling datasets of dengue virus serotype 2 (DENV2) patients. We found overexpressed genes in dengue patients that can interrupt cell cycle progression and phase transitions of mitosis inside the host to favour the viral replication process. These DEGs were associated with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways such as cell cycle and DNA replication. A protein interaction network consisting of these significant pathways was also constructed using STRING. Futher, the traditional Chinese medicine (TCM) compounds from Ganoderma lucidum were screened to target DENV2 envelope protein, which was crucial for viral fusion activity. Docking, orbital energy, and toxicity prediction analysis revealed that naringenin was the best antiviral candidate. Following molecular dynamics simulations, the predicted binding energy of the protein-naringenin system using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach was slightly greater than the control system. It is recommended to perform in vitro inhibition of naringenin against DENV2 and use our findings to complement the experimental data obtained.