Evidence map›Paper›PMID 40729046›Full record

ArticleCurrent issues in molecular biology2025

Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases.

Paul Andrei Negru, Andrei-Flavius Radu, Ada Radu, Delia Mirela Tit, Gabriela Bungau

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Article in Current issues in molecular biology, 2025. 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Paul Andrei NegruDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania.
Andrei-Flavius RaduDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania.ORCID 0000-0002-7625-8177
Ada RaduDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania.
Delia Mirela TitDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania.ORCID 0000-0002-0296-6592
Gabriela BungauDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global impact of the COVID-19 crisis has underscored the need for novel therapeutic candidates capable of efficiently targeting essential viral proteins. Existing therapeutic strategies continue to encounter limitations such as reduced efficacy against emerging variants, safety concerns, and suboptimal pharmacodynamics, which emphasize the potential of natural-origin compounds as supportive agents with immunomodulatory, anti-inflammatory, and antioxidant benefits. The present study significantly advances prior molecular docking research through comprehensive virtual screening of structurally related analogs derived from antiviral phytochemicals. These compounds were evaluated specifically against the SARS-CoV-2 main protease (3CLpro) and papain-like protease (PLpro). Utilizing chemical similarity algorithms via the ChEMBL database, over 600 candidate molecules were retrieved and subjected to automated docking, interaction pattern analysis, and comprehensive ADMET profiling. Several analogs showed enhanced binding scores relative to their parent scaffolds, with CHEMBL1720210 (a shogaol-derived analog) demonstrating strong interaction with PLpro (-9.34 kcal/mol), and CHEMBL1495225 (a 6-gingerol derivative) showing high affinity for 3CLpro (-8.04 kcal/mol). Molecular interaction analysis revealed that CHEMBL1720210 forms hydrogen bonds with key PLpro residues including GLY163, LEU162, GLN269, TYR265, and TYR273, complemented by hydrophobic interactions with TYR268 and PRO248. CHEMBL1495225 establishes multiple hydrogen bonds with the 3CLpro residues ASP197, ARG131, TYR239, LEU272, and GLY195, along with hydrophobic contacts with LEU287. Gene expression predictions via DIGEP-Pred indicated that the top-ranked compounds could influence biological pathways linked to inflammation and oxidative stress, processes implicated in COVID-19's pathology. Notably, CHEMBL4069090 emerged as a lead compound with favorable drug-likeness and predicted binding to PLpro. Overall, the applied in silico framework facilitated the rational prioritization of bioactive analogs with promising pharmacological profiles, supporting their advancement toward experimental validation and therapeutic exploration against SARS-CoV-2.

Indexed as

3ClproAllium sativumCOVID-19in silicomolecular dockingPLproSARS-CoV-2virtual screeningZingiber officinale

Identifiers

PMID40729046
PMCPMC12294011

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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.