SARS-CoV-2 infections are highly correlated with the overexpression of pro-inflammatory cytokines in what is known as a cytokine storm, leading to high fatality rates. Such infections are accompanied by SIRS, ARDS, and sepsis, suggesting a potential link between the three phenotypes. Currently, little is known about the transcriptional similarity between these conditions. Herein, weighted gene co-expression network analysis (WGCNA) clustering was applied to RNA-seq datasets (GSE147902, GSE66890, GSE74224, GSE177477) to identify modules of highly co-expressed and correlated genes, cross referenced with dataset GSE160163, across the samples. To assess the transcriptome similarities between the conditions, module preservation analysis was performed and functional enrichment was analyzed in DAVID webserver. The hub genes of significantly preserved modules were identified, classified into upregulated or downregulated, and used to screen candidate drugs using Connectivity Map (CMap) to identify repurposed drugs. Results show that several immune pathways (chemokine signaling, NOD-like signaling, and Th1 and Th2 cell differentiation) are conserved across the four diseases. Hub genes screened using intramodular connectivity show significant relevance with the pathogenesis of cytokine storms. Transcriptomic-driven drug repurposing identified seven candidate drugs (SB-202190, eicosatetraenoic-acid, loratadine, TPCA-1, pinocembrin, mepacrine, and CAY-10470) that targeted several immune-related processes. These identified drugs warrant further study into their efficacy for treating cytokine storms, and in vitro and in vivo experiments are recommended to confirm the findings of this study.

Cytokine storms, an overaggressive immune response due to the overexpression of pro-inflammatory cytokines, have been identified to play a significant role in COVID-19 infections. Studies have shown that TNF-α and IFN-γ are integral to the process, however, its genetic mechanisms have yet to be fully elucidated. Herein, the key changes in the gene expression of TNF-α and IFN-γ induced cytokine storms are identified through differential gene analysis on the publicly available GEO GSE160163 dataset. GO and KEGG enrichment were used to annotate identified DEGs, and a PPI network was constructed based on the STRING database. A total of 446 differentially expressed genes were identified. Up-regulated genes and downregulated genes were enriched in viral immune response and infection pathways, and steroid biosynthesis and metabolic pathways, respectively. PPI construction revealed 1,834 interactions between 428 proteins, indicating their biological connectivity. Module analysis identified nine (9) hub genes: STAT1, CXCL10, CD274, CXCL9, IRF1, PSMB9, CD86, STAT3, and CXCR4, involved in viral immune response and three (3) significant modules involved in NOD-like receptor signaling, steroid biosynthesis, and viral infections. These identified DEGs, hub genes, and their respective enriched pathways aid us in understanding the molecular mechanisms of cytokine storms, as well as provide potential gene targets and druggable receptors for the treatment of cytokine storms.

The biological origin of COVID-19 is linked to three pathophysiological conditions: immunosuppression, viral infection, and inflammation. In the Philippines, nine alkaloids with potential antiviral and anti-inflammatory effects have been isolated from two plants, Uncaria perrottetii and Uncaria lanosa f. philippinensis, and their potential for COVID-19 therapy were investigated. Results showed that mitraphylline (L5) and uncarine B (L6) are two potential candidates as they exhibited the best binding energy score, lowest binding interaction energies, and lowest RMSD score. MMPBSA analysis indicated that complex binding energies of -128.295 ± 16.787 kJ/mol and -44.940 ± 10.918 for A2AR-5 and 3CL-6, suggesting that mitraphylline is a potential competitive antagonist in A2AR of caffeine, which is a known antagonist and inhibitor of the receptors, and uncarine B is a candidate inhibitor of 3CL protease.

On January 31, 2020, WHO declared the global outbreak of novel Coronavirus as a public health emergency of international concern. The biological origin of COVID-19 is caused by three primary pathophysiological conditions: immunosuppression, viral infection, and inflammation. In the Philippines, nine alkaloids with potential antiviral and anti-inflammatory effects have been isolated from two plants, Uncaria perrottetii and Uncaria lanosa f. philippinensis. The binding site of A2AR was proven to be pocket 0, which is similar to the literature. Two drug candidates showed the best result for molecular docking: mitraphylline and rauniticine-allo-oxindole A for A2AR and 3CLpro receptors. Mitraphylline candidate showed the lowest free energy scores and RMSD scores. This study is extended to other in silico tests to prove the impact of the alkaloid against COVID-19.

White Feces Syndrome (WFS) is a disease that causes serious problems in the shrimp aquaculture industry and is highly linked to two bacterial species, namely, Enterocytozoon hepatopenaei (EHP) and Gram-negative Vibrio species. Due to the emergence of new diseases in shrimps and their unclear etiology, such as WFS, there is a need for the development of new therapeutic strategies that can improve the immunity of shrimps. Thus, in this study, we determined glycosidic compounds which can serve as immunostimulants that have high affinity towards P. monodon shrimp TLR9 to induce the NF-κB signaling pathway and strengthen shrimp immunity against viral and bacterial diseases. The glycosidic compounds were obtained from the Immulina polysaccharide. The protein structure was acquired through homology modeling using mouse TLR3 (SMTL ID: 7c77.1) as a template using the SWISS-MODEL webserver. Based on the docking studies, N-acetyl-glucosamine (ca. -6.99 kcal/mol), 2,3-methylfucose (ca. -6.78 kcal/mol), and 2-methyl glycose (ca. -6.66 kcal/mol) were the top-scoring compounds which have high binding affinity towards the target protein. By visualizing the ligand-protein interactions, we learned that ASN512 was the common binding residue among most of the top-scoring compounds and plays a crucial role in ligand-protein binding. Based on the MD studies, all compounds showed low RMSD values, except N-acetyl-glucosamine, indicating good ligand binding to the target protein. In the MMPBSA studies, we found that 2,3-methylfucose had the lowest average binding energy (ca. -41.507 ± 88.52); hence, this glycosidic compound shows the highest affinity towards shrimp TLR9. To conclude, all three top-scoring compounds have highly favorable agonistic binding towards P. monodon TLR9 given their low average binding energy values. To further affirm our conclusions, we recommend the use of in vivo and in vitro tests, as well as longer MD studies for more accurate simulations.