Evidence map›Paper›PMID 34324152›Full record

ArticleApplied biochemistry and biotechnology2021

Synthesis and Identification of Novel Potential Molecules Against COVID-19 Main Protease Through Structure-Guided Virtual Screening Approach.

Youness El Bakri, El Hassane Anouar, Sajjad Ahmad, Amal A Nassar, Mohamed Labd Taha, Joel T Mague, Lhoussaine El Ghayati, El Mokhtar Essassi

Open access · bronzeAbstract read
In one paragraph

Article in Applied biochemistry and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 11% of its field
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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. TargetingMolecules (Basel, Switzerland) · 2023
    Article
  3. Article
  4. Article
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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

8 authors at 6 institutions in 6 countries.

Youness El BakriLaboratoire de Chimie Organique Hétérocyclique, URAC 21, Pôle de Compétences Pharmaco-Chimie, Faculté Des Sciences, Université Mohammed V, BP 10014, Rabat, Morocco. yns.elbakri@gmail.com.ORCID http://orcid.org/0000-0002-5759-6568
El Hassane AnouarDepartment of Chemistry, College of Science and Humanities, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Sajjad AhmadDepartment of Health and Biological Sciences, Abasyn University, Peshawar, 25000, Pakistan.
Amal A NassarDepartment of Chemistry, College of Science and Humanities, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Mohamed Labd TahaLaboratoire of Chemistry and Environment, Applied Bioorganic Chemistry Team, Faculty of Scinces, Ibn Zohr University, Agadir, Morocco.
Joel T MagueDepartment of Chemistry, Tulane University, New Orleans, LA, 70118, USA.
Lhoussaine El GhayatiLaboratoire de Chimie Organique Hétérocyclique, URAC 21, Pôle de Compétences Pharmaco-Chimie, Faculté Des Sciences, Université Mohammed V, BP 10014, Rabat, Morocco.
El Mokhtar EssassiLaboratoire de Chimie Organique Hétérocyclique, URAC 21, Pôle de Compétences Pharmaco-Chimie, Faculté Des Sciences, Université Mohammed V, BP 10014, Rabat, Morocco.
Mohammed V University · MAPrince Sattam Bin Abdulaziz University · SAAbasyn University · PKSouth Ural State University · RUTulane University · USUniversité Ibn Zohr · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus disease that arises in the end of 2019 (COVID-19) in Wuhan, China, has rapidly spread over the globe and was considered as a world pandemic. Currently, various antiviral therapies or vaccines are available, and many researches are ongoing for further treatments. Targeting the coronavirus' main protease (key enzyme: 3CLpro) is growing in importance in anti-SARS-CoV-2 drug discovery process. The present study aims at predicting the antiviral activity of two novel compounds using in silico approaches that might become potential leads against SARS-CoV-2. The 3D structures of the new compounds are elucidated by single-crystal X-ray techniques. The interactions between different units of 4 and 5 were emphasized by analyzing their corresponding Hirshfeld surfaces and ESP plots. NBO and FMO analyses were investigated as well. Molecular docking combined with molecular dynamics simulations (MDs) was performed to investigate the binding modes and molecular interactions of 4 and 5 with the amino acids of coronavirus main protease (6LU7) protein. The best docking scores were obtained for both ligands through the major binding interactions via hydrogen/hydrophobic bonds with the key amino acids in the active site: HIS41, CYS145, MET49, MET165, HIS172, and GLU166 amino acids. A MD simulation study was also performed for 100 ns to validate the stability behavior of the main protease 3CLpro-ligand complexes. The MD simulation study successfully confirmed the stability of the ligands in the binding site as potent anti-SARS-CoV-2 (COVID-19) inhibitors. Additionally, MMPBSA energy of both docked complexes was determined as a validation assay of docking and MD simulations to validate compound conformation and interaction stability with 3CLpro. The synthesized compounds might be helpful in the fight against COVID-19 prior to biological activity confirmation in vitro and in vivo.

Indexed as

Antiviral AgentsBinding SitesCatalytic DomainCoronavirus 3C ProteasesCOVID-19Drug DiscoveryHumansMolecular Docking SimulationMolecular Dynamics SimulationProtease InhibitorsSARS-CoV-2Antiviral AgentsCoronavirus 3C ProteasesProtease InhibitorsBenzodiazepineCOVID-19Molecular dockingMolecular dynamics simulationQuinoxalineSARS-CoV-2

Identifiers

PMID34324152
PMCPMC8319192
OpenAlexW3185886782

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.