Evidence map›Paper›PMID 40678415›Full record

ArticleTurkish journal of biology = Turk biyoloji dergisi2025

FDA-approved drugs as potential covalent inhibitors of key SARS-CoV-2 proteins: an in silico approach.

Murat Serilmez, Anwar Abuelrub, Ismail Erol, Serdar Durdaği

Abstract read
In one paragraph

Article in Turkish journal of biology = Turk biyoloji dergisi, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Murat SerilmezDepartment of Basic Oncology, Oncology Institute, Istanbul University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0001-8502-2505
Anwar AbuelrubComputational Drug Design Center (HİTMER), Bahçeşehir University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0003-0043-5314
Ismail ErolComputational Drug Design Center (HİTMER), Bahçeşehir University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0001-8256-6283
Serdar DurdağiComputational Drug Design Center (HİTMER), Bahçeşehir University, İstanbul, Turkiye.ORCID https://orcid.org/0000-0002-0426-0905

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/aim: The COVID-19 pandemic caused by SARS-CoV-2 necessitated rapid development of effective therapeutics, prompting this study to identify potential inhibitors targeting key viral and host proteins: RNA-dependent RNA polymerase (RdRp), main protease (Mpro), transmembrane serine protease 2 (TMPRSS2), and angiotensin-converting enzyme 2 (ACE2). Methods: We used covalent docking and molecular dynamics (MD) simulations to screen FDA-approved compounds against these targets using diverse covalent reaction mechanisms. Top-ranking compounds underwent further evaluation through MD simulations to assess binding stability and conformational dynamics. Results: Several promising drug repurposing candidates were identified: bremelanotide, lanreotide, histrelin, and leuprolide as potential RdRp inhibitors; azlocillin, cefiderocol, and sultamicillin for Mpro inhibition; tenapanor, isavuconazonium, and ivosidenib targeting TMPRSS2; and cefiderocol, cefoperazone, and ceftolozane as potential ACE2 inhibitors. Conclusion: This study provides valuable insights into repurposing existing drugs as potential COVID-19 therapeutics by targeting crucial viral proteins. However, further experimental validation and preclinical studies are necessary to confirm the efficacy and safety of these compounds before consideration for clinical application.

Indexed as

covalent dockingCOVID-19molecular dynamics simulationmolecular mechanics-generalized Born surface area

Identifiers

PMID40678415
PMCPMC12266346

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.