Transcription factor NF-κB as target for SARS-CoV-2 drug discovery efforts using inflammation-based QSAR screening model.

Anti-Inflammation COVID-19 Drug development IkBα Inflammation NF-kappaB NF-κB inhibitor Nuclear factor kappa B QSAR SARS-CoV-2 Virtual screening

Journal

Journal of molecular graphics & modelling
ISSN: 1873-4243
Titre abrégé: J Mol Graph Model
Pays: United States
ID NLM: 9716237

Informations de publication

Date de publication:
11 2021
Historique:
received: 20 12 2020
revised: 12 06 2021
accepted: 14 06 2021
pubmed: 27 7 2021
medline: 15 9 2021
entrez: 26 7 2021
Statut: ppublish

Résumé

NF-κB is a central regulator of immunity and inflammation. It is suggested that the inflammatory response mediated by SARS-CoV-2 is predominated by NF-κB activation. Thus, NF-κB inhibition is considered a potential therapeutic strategy for COVID-19. The aim of this study was to identify potential anti-inflammation lead molecules that target NF-κB using a quantitative structure-activity relationships (QSAR) model of currently used and investigated anti-inflammatory drugs as the basis for screening. We applied an integrated approach by starting with the inflammation-based QSAR model to screen three libraries containing more than 220,000 drug-like molecules for the purpose of finding potential drugs that target the NF-κB/IκBα p50/p65 (RelA) complex. We also used QSAR models to rule out molecules that were predicted to be toxic. Among screening libraries, 382 molecules were selected as potentially nontoxic and were analyzed further by short and long molecular dynamics (MD) simulations and free energy calculations. We have discovered five hit ligands with highly predicted anti-inflammation activity and nearly no predicted toxicities which had strongly favorable protein-ligand interactions and conformational stability at the binding pocket compared to a known NF-κB inhibitor (procyanidin B2). We propose these hit molecules as potential NF-κB inhibitors which can be further investigated in pre-clinical studies against SARS-CoV-2 and may be used as a scaffold for chemical optimization and drug development efforts.

Identifiants

pubmed: 34311260
pii: S1093-3263(21)00139-X
doi: 10.1016/j.jmgm.2021.107968
pmc: PMC8219481
pii:
doi:

Substances chimiques

NF-kappa B 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107968

Informations de copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

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Auteurs

Tarek Kanan (T)

School of Medicine, Bahcesehir University, Istanbul, Turkey; Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey.

Duaa Kanan (D)

School of Medicine, Bahcesehir University, Istanbul, Turkey; Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey.

Ebrahim Jaafar Al Shardoub (EJ)

School of Medicine, Bahcesehir University, Istanbul, Turkey.

Serdar Durdagi (S)

Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey; Neuroscience Program, Institute of Health Sciences, Bahcesehir University, Istanbul, Turkey. Electronic address: serdar.durdagi@med.bau.edu.tr.

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