3.8 Article

Network-Based Prediction of Side Effects of Repurposed Antihypertensive Sartans against COVID-19 via Proteome and Drug-Target Interactomes

Journal

PROTEOMES
Volume 11, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/proteomes11020021

Keywords

angiotensin receptor blockers; Sartans; coronavirus disease 19; angiotensin-converting enzyme 2; protein-protein interaction networks; drug-drug interaction prediction; off-target interaction prediction; gene ontology

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The potential of targeting the RAAS as a treatment for COVID-19 is being investigated. This study analyzed the potential side effects and off-target effects of antihypertensive drugs, ARBs, and Pfizer's antiviral drug, Paxlovid, for COVID-19 treatment. The findings compared the effects and possible risks of both drug categories.
The potential of targeting the Renin-Angiotensin-Aldosterone System (RAAS) as a treatment for the coronavirus disease 2019 (COVID-19) is currently under investigation. One way to combat this disease involves the repurposing of angiotensin receptor blockers (ARBs), which are antihypertensive drugs, because they bind to angiotensin-converting enzyme 2 (ACE2), which in turn interacts with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. However, there has been no in silico analysis of the potential toxicity risks associated with the use of these drugs for the treatment of COVID-19. To address this, a network-based bioinformatics methodology was used to investigate the potential side effects of known Food and Drug Administration (FDA)-approved antihypertensive drugs, Sartans. This involved identifying the human proteins targeted by these drugs, their first neighbors, and any drugs that bind to them using publicly available experimentally supported data, and subsequently constructing proteomes and protein-drug interactomes. This methodology was also applied to Pfizer's Paxlovid, an antiviral drug approved by the FDA for emergency use in mild-to-moderate COVID-19 treatment. The study compares the results for both drug categories and examines the potential for off-target effects, undesirable involvement in various biological processes and diseases, possible drug interactions, and the potential reduction in drug efficiency resulting from proteoform identification.

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