Evidence map›Paper›PMID 42737581›Full record

ArticleInternational journal of molecular sciences2026

Identification of Potential SARS-CoV-2 Main Protease (MPro) Inhibitors Through Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation Approaches.

Mohd Yasir Khan, Farah Maarfi, Abid Ullah Shah, Nithyadevi Duraisamy, Mohammed Cherkaoui, Maged Gomaa Hemida

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

6 authors.

Mohd Yasir KhanDepartment of Digital Engineering and Artificial Intelligence, College of Science, Long Island University, Brooklyn, NY 11201, USA.ORCID 0000-0003-1107-7428
Farah MaarfiDepartment of Digital Engineering and Artificial Intelligence, College of Science, Long Island University, Brooklyn, NY 11201, USA.ORCID 0000-0002-9102-1960
Abid Ullah ShahDepartment of Veterinary Biomedical Sciences, Lewyt College of Veterinary Medicine, Long Island University, 720 Northern Boulevard, Brookville, NY 11548, USA.
Nithyadevi DuraisamyDepartment of Digital Engineering and Artificial Intelligence, College of Science, Long Island University, Brooklyn, NY 11201, USA.ORCID 0000-0001-9943-0008
Mohammed CherkaouiDepartment of Digital Engineering and Artificial Intelligence, College of Science, Long Island University, Brooklyn, NY 11201, USA.
Maged Gomaa HemidaDepartment of Veterinary Biomedical Sciences, Lewyt College of Veterinary Medicine, Long Island University, 720 Northern Boulevard, Brookville, NY 11548, USA.ORCID 0000-0003-1663-5820

Funding

United States Department of Agriculture NI26AHDRXXXXG063-0001
6 · The paper itself

Abstract

The main protease (MPro) of coronaviruses (CoVs) is an essential enzyme involved in viral replication and represents an attractive target for antiviral drug discovery. Based on the similar binding pocket residues within the MPro of different CoVs, this study aimed to identify potential inhibitors of SARS-CoV-2 MPro from PDB ID 6M2N using integrated computational approaches. Interaction-based pharmacophore modeling, virtual screening, molecular docking, MM-GBSA binding energy calculation, and molecular dynamics simulation (MDS) were performed using BIOVIA Discovery Studio. The validated pharmacophore model was utilized to screen the ZINC database, followed by docking and 100 ns MDS analyses of the top-ranked compounds. The pharmacophore model 01 demonstrated favorable predictive performance (AUC = 0.781). Virtual screening identified 483 compounds, from which 15 compounds were selected for docking studies. Among them, ZINC95473654 (Lig-1), ZINC95473725 (Lig-2), and ZINC08792368 (Lig-3) exhibited strong binding affinity toward MPro. Lig-1 demonstrated the best docking score and binding free energy, along with stable interactions with key catalytic residues HIS41, CYS145, and GLU166. MDS analyses further confirmed that Lig-1, Lig-2 and Lig-3 maintained stable conformations. The hydrogen bond distance monitoring and post MDS-MM-GBSA results suggest Lig-1 followed by Lig-3 as an inhibitor for MPro and persistent intermolecular interactions throughout the 100 ns simulation period. The findings suggest that Lig-1, followed by Lig-3, may serve as promising computational lead compounds targeting SARS-CoV-2 MPro, representing promising candidates for further experimental validation.

Indexed as

Antiviral AgentsBetacoronavirusProtease InhibitorsSARS-CoV-2Viral Nonstructural ProteinsBinding SitesCoronavirus 3C ProteasesCysteine EndopeptidasesHumansMolecular Docking SimulationMolecular Dynamics SimulationPharmacophoreProtein BindingAntiviral AgentsCoronavirus 3C ProteasesCysteine EndopeptidasesProtease InhibitorsViral Nonstructural Proteinscatalytic dyadcoronaviruses (CoVs)main protease (MPro)molecular dockingmolecular dynamics simulation (MDS)pharmacophore modelingvirtual screening

Identifiers

PMID42737581
PMCPMC13566167

What Socratic 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 Socratic graph.