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.

过去二十年来，登革热病例激增。人们仍在不断努力，以更深入地了解这种虫媒病毒疾病并确定生物活性抗病毒药物。在本研究中，通过生物信息学分析来识别登革热病毒血清型 2 (DENV2) 患者表达谱数据集中的差异表达基因 (DEG)。我们发现登革热患者中过度表达的基因可以中断宿主体内的细胞周期进程和有丝分裂的相变，以有利于病毒复制过程。这些差异基因与京都基因和基因组百科全书 (KEGG) 途径（例如细胞周期和 DNA 复制）相关。还使用 STRING 构建了由这些重要途径组成的蛋白质相互作用网络。此外，还筛选了灵芝中的中药化合物，以靶向 DENV2 包膜蛋白，这对于病毒融合活性至关重要。对接、轨道能量和毒性预测分析表明柚皮素是最好的抗病毒候选药物。经过分子动力学模拟，使用分子力学泊松-玻尔兹曼表面积（MM-PBSA）方法预测的蛋白质-柚皮素系统的结合能略大于对照系统。建议对 DENV2 进行柚皮素体外抑制，并使用我们的发现来补充获得的实验数据。