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

Authors :
Despoina P. Kiouri
Charalampos Ntallis
Konstantinos Kelaidonis
Massimiliano Peana
Sotirios Tsiodras
Thomas Mavromoustakos
Alessandro Giuliani
Harry Ridgway
Graham J. Moore
John M. Matsoukas
Christos T. Chasapis
Source :
Proteomes, Vol 11, Iss 2, p 21 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

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.

Details

Language :
English
ISSN :
22277382
Volume :
11
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Proteomes
Publication Type :
Academic Journal
Accession number :
edsdoj.b9dba9a5c93f4d56b563f3e09625703a
Document Type :
article
Full Text :
https://doi.org/10.3390/proteomes11020021