Computational and Experimental Approaches Identify Beta-Blockers as Potential SARS-CoV‑2 Spike Inhibitors

Finding antivirals for SARS-CoV-2 is still a major challenge, and many computational and experimental approaches have been employed to find a solution to this problem. While the global vaccination campaigns are the primary driver of controlling the current pandemic, orally bioavailable small-molecule drugs and biologics are critical to overcome this global issue. Improved therapeutics and prophylactics are required to treat people with circulating and emerging new variants, addressing severe infection, and people with underlying or immunocompromised conditions. The SARS-CoV-2 envelope spike is a challenging target for viral entry inhibitors. Pindolol presented a good docking score in a previous virtual screening using computational docking calculations after screening a Food and Drug Administration (FDA)-approved drug library of 2400 molecules as potential candidates to block the SARS-CoV-2 spike protein interaction with the angiotensin-converting enzyme 2 (ACE-2). Here, we expanded the computational evaluation to identify five beta-blockers against SARS-CoV-2 using several techniques, such as microscale thermophoresis, NanoDSF, and <em>in vitro</em> assays in different cell lines. These data identified carvedilol with a <em>K</em> <sub>d</sub> of 364 &plusmn; 22 nM for the SARS-CoV-2 spike and <em>in vitro</em> activity (EC<sub>50</sub> of 7.57 &mu;M, CC<sub>50</sub> of 18.07 &mu;M) against SARS-CoV-2 in Calu-3 cells. We have shown how we can apply multiple computational and experimental approaches to find molecules that can be further optimized to improve anti-SARS-CoV-2 activity.

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Publication Details

Journal
UNC Libraries
Published
2025-04-22
DOI
https://doi.org/10.17615/w8bn-jb15
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

Computational and Experimental Approaches Identify Beta-Blockers as Potential SARS-CoV‑2 Spike Inhibitors

Gabriel Gonçalves Dias, Thiago Moreno L. Souza, Kenneth H. Pearce, Melina Mottin et al.
UNC Libraries
Computational Drug Discovery Methods
article

Computational and Experimental Approaches Identify Beta-Blockers as Potential SARS-CoV‑2 Spike Inhibitors

Gabriel Gonçalves Dias, Thiago Moreno L. Souza, Kenneth H. Pearce, Melina Mottin, Carolina Q. Sacramento, Eric M. Merten, Fábio Trindade Maranhão Costa, Tatyana Almeida Tavella, Natalia Fintelman‐Rodrigues, Ana C. Puhl, Lakshmanane Premkumar, Carolina Horta Andrade, Paulo Ricardo Pimenta da Silva Ramos, Sean Ekins, Suelen da Silva Gomes Dias, Jairo R. Temerozo
article en

Abstract

Finding antivirals for SARS-CoV-2 is still a major challenge, and many computational and experimental approaches have been employed to find a solution to this problem. While the global vaccination campaigns are the primary driver of controlling the current pandemic, orally bioavailable small-molecule drugs and biologics are critical to overcome this global issue. Improved therapeutics and prophylactics are required to treat people with circulating and emerging new variants, addressing severe infection, and people with underlying or immunocompromised conditions. The SARS-CoV-2 envelope spike is a challenging target for viral entry inhibitors. Pindolol presented a good docking score in a previous virtual screening using computational docking calculations after screening a Food and Drug Administration (FDA)-approved drug library of 2400 molecules as potential candidates to block the SARS-CoV-2 spike protein interaction with the angiotensin-converting enzyme 2 (ACE-2). Here, we expanded the computational evaluation to identify five beta-blockers against SARS-CoV-2 using several techniques, such as microscale thermophoresis, NanoDSF, and <em>in vitro</em> assays in different cell lines. These data identified carvedilol with a <em>K</em> <sub>d</sub> of 364 &plusmn; 22 nM for the SARS-CoV-2 spike and <em>in vitro</em> activity (EC<sub>50</sub> of 7.57 &mu;M, CC<sub>50</sub> of 18.07 &mu;M) against SARS-CoV-2 in Calu-3 cells. We have shown how we can apply multiple computational and experimental approaches to find molecules that can be further optimized to improve anti-SARS-CoV-2 activity.

UNC Libraries
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 72%
Computational Drug Discovery Methods
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