ArticleScientific reports2025
Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Exploring the Anticancer Potential of Novel Piperidine-Embedded Isoxazol-Triazole Conjugates Against MCF-7 Human Breast Adenocarcinoma Cell Line: Design, Synthesis, In Silico, and In Vitro Investigations.Chemistry & biodiversity · 2026Article
- Machine learning-driven prioritization and experimental validation of traditional Chinese medicine-derived STING-inhibitory candidates.Molecular diversity · 2026Article
- Molecular Dynamics Simulations and Current Trends in Designing New Antivirals Targeting Proteases: A Review from 2018 to 2025.Current drug targets · 2026Review
- Immunoinformatics approach to engineer a multi-epitope vaccine against SdrG in skin commensal Staphylococcus epidermidis.PloS one · 2026Article
- Insights from integrated covalent docking and molecular dynamics simulations of nirmatrelvir analogs as potential SARS-CoV-2 MScientific reports · 2025Article
- An Interpretable Deep Learning and Molecular Docking Framework for Repurposing Existing Drugs as Inhibitors of SARS-CoV-2 Main Protease.Molecules (Basel, Switzerland) · 2025Article
- Pharmacological Evaluation of active compounds in papaya associated with thrombocytopenia inhibition in dengue patients through in silico approaches.Scientific reports · 2025Article
- Antagonistic Trends Between Binding Affinity and Drug-Likeness in SARS-CoV-2 Mpro Inhibitors Revealed by Machine Learning.Viruses · 2025Article
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Authors and funding
10 authors.
Funding
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Abstract
The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced computational techniques such as molecular docking and molecular dynamics simulations were used to screen a series of antiviral compounds for their potential inhibitory effect on the SARS-CoV-2 Mpro. A comprehensive analysis of compounds from the ChemDiv and PubChem databases was performed. The physicochemical properties, pharmacokinetics, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiles were evaluated to determine drug similarity and safety. Compound 4896 - 4038 proved to be the most promising candidate. It exhibited a favorable balance between molecular weight (491.06) and lipophilicity (logP 3.957), high intestinal absorption (92.119%), and broad tissue distribution (VDss of 0.529), indicating good oral bioavailability and therapeutic potential. Molecular docking studies showed that 4896 - 4038 has a strong binding affinity to the active site of Mpro and forms key interactions, such as hydrogen bonds, carbon-hydrogen bonds, pi-sulfur, and multiple van der Waals and pi-pi stacked bonds. The binding energy was comparable to that of the reference drug X77, indicating potential efficacy. Molecular dynamics simulations over 300 ns confirmed the stability of the Mpro/4896 - 4038 complex of protein-ligand. Free energy landscape mapping and MM/PBSA calculations further substantiated the favorable binding and stability of the complex. Importantly, 4896 - 4038 exhibited a comparatively favorable safety profile. In summary, compound 4896 - 4038 shows significant potential as a potent SARS-CoV-2 Mpro inhibitor, combining potent inhibitory activity with favorable pharmacokinetic and safety profiles. These results support the further development of 4896 - 4038 as a promising therapeutic agent in the fight against COVID-19 that warrants experimental validation and clinical investigation.
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