Multi-Tissue Transcriptomic-Informed In Silico Investigation of Drugs for the Treatment of Dengue Fever Disease

Abstract

Transcriptomics, proteomics and pathogen-host interactomics data are being explored for the in silico–informed selection of drugs, prior to their functional evaluation. The effectiveness of this kind of strategy has been put to the test in the current COVID-19 pandemic, and it has been paying off, leading to a few drugs being rapidly repurposed as treatment against SARS-CoV-2 infection. Several neglected tropical diseases, for which treatment remains unavailable, would benefit from informed in silico investigations of drugs, as performed in this work for Dengue fever disease. We analyzed transcriptomic data in the key tissues of liver, spleen and blood profiles and verified that despite transcriptomic differences due to tissue specialization, the common mechanisms of action, “Adrenergic receptor antagonist”, “ATPase inhibitor”, “NF-kB pathway inhibitor” and “Serotonin receptor antagonist”, were identified as druggable (e.g., oxprenolol, digoxin, auranofin and palonosetron, respectively) to oppose the effects of severe Dengue infection in these tissues. These are good candidates for future functional evaluation and clinical trials.

Integrative systems vaccinology identification of shared gene signatures between natural dengue infection and vaccination trials

“…Two of these multi-study reports identifying immunological signatures defining dengue severity and progression found enrichment of IFN-associated DEGs that control signaling pathways pivotal for antiviral immune responses 55,56 . Moreover, a recent multi-tissue transcriptome approach, developed to identify liver, spleen and blood signatures, revealed novel candidate targets for therapeutic strategies to reduce dengue morbidity and mortality 57 .…”