Methods: Each 24-well plate of Vero cells infected with all four DENV serotypes, singly, was subjected to treatments with various doses of AR-12. Following 48 h of incubation, inhibitory efficacies of AR-12 against the different DENV serotypes were evaluated by conducting a virus yield reduction assay whereby DENV RNA copy numbers present in the collected supernatant were quantified using qRT-PCR. The underlying mechanism(s) possibly involved in the compound's inhibitory activities were then investigated by performing molecular docking on several potential target human and DENV protein domains.
Results: The qRT-PCR data demonstrated that DENV-3 was most potently inhibited by AR-12, followed by DENV-1, DENV-2 and DENV-4. Our molecular docking findings suggested that AR-12 possibly exerted its inhibitory effects by interfering with the chaperone activities of heat shock proteins.
Conclusions: These results serve as vital information for the design of future studies involving in vitro mechanistic studies and animal models, aiming to decipher the potential of AR-12 as a potential therapeutic option for DENV infection.
METHODS: Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.
RESULTS: The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.
CONCLUSIONS: Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.