Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases
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 sub...
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MDPI AG
2025-07-01
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| Series: | Current Issues in Molecular Biology |
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| author | Paul Andrei Negru Andrei-Flavius Radu Ada Radu Delia Mirela Tit Gabriela Bungau |
| author_facet | Paul Andrei Negru Andrei-Flavius Radu Ada Radu Delia Mirela Tit Gabriela Bungau |
| author_sort | Paul Andrei Negru |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9a2b5710be404f09b265db8be8dd23d7 |
| institution | Kabale University |
| issn | 1467-3037 1467-3045 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Current Issues in Molecular Biology |
| spelling | doaj-art-9a2b5710be404f09b265db8be8dd23d72025-08-20T03:36:14ZengMDPI AGCurrent Issues in Molecular Biology1467-30371467-30452025-07-0147757710.3390/cimb47070577Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 ProteasesPaul Andrei Negru0Andrei-Flavius Radu1Ada Radu2Delia Mirela Tit3Gabriela Bungau4Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaThe 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.https://www.mdpi.com/1467-3045/47/7/577COVID-19in silicoSARS-CoV-2molecular dockingvirtual screening3Clpro |
| spellingShingle | Paul Andrei Negru Andrei-Flavius Radu Ada Radu Delia Mirela Tit Gabriela Bungau Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases Current Issues in Molecular Biology COVID-19 in silico SARS-CoV-2 molecular docking virtual screening 3Clpro |
| title | Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases |
| title_full | Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases |
| title_fullStr | Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases |
| title_full_unstemmed | Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases |
| title_short | Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases |
| title_sort | computational evaluation and multi criteria optimization of natural compound analogs targeting sars cov 2 proteases |
| topic | COVID-19 in silico SARS-CoV-2 molecular docking virtual screening 3Clpro |
| url | https://www.mdpi.com/1467-3045/47/7/577 |
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