Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis
Abstract This study employs structural bioinformatics approaches to identify and evaluate potential drug targets within the Hepatitis C virus (HCV) proteome. Through integration of homology modeling, molecular docking, and molecular dynamics simulations, we analyzed the structural features and drugg...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-12563-w |
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| author | Miao Qu Mingzhu Gao Xisheng Sang Miao Yu Zihe Guan Weizhi Chang |
| author_facet | Miao Qu Mingzhu Gao Xisheng Sang Miao Yu Zihe Guan Weizhi Chang |
| author_sort | Miao Qu |
| collection | DOAJ |
| description | Abstract This study employs structural bioinformatics approaches to identify and evaluate potential drug targets within the Hepatitis C virus (HCV) proteome. Through integration of homology modeling, molecular docking, and molecular dynamics simulations, we analyzed the structural features and druggability of key HCV proteins. The research focused on predicting binding sites, evaluating protein-ligand interactions, and assessing the therapeutic potential of identified targets. Our findings revealed promising drug targets including the NS3 protease, NS5B polymerase, core protein, and NS5A, with detailed characterization of their binding pockets and interaction patterns. The study provides structural insights for rational drug design against HCV and demonstrates the utility of computational approaches in antiviral drug discovery. While experimental validation is needed, these results contribute to the development of novel anti-HCV therapeutics and highlight potential strategies for targeted intervention. |
| format | Article |
| id | doaj-art-19f46420dfe5427484d96aae83aada7b |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-19f46420dfe5427484d96aae83aada7b2025-08-20T04:03:01ZengNature PortfolioScientific Reports2045-23222025-07-0115111210.1038/s41598-025-12563-wStructural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysisMiao Qu0Mingzhu Gao1Xisheng Sang2Miao Yu3Zihe Guan4Weizhi Chang5School of basic Medicine, Heilongjiang University of Chinese MedicineSchool of basic Medicine, Heilongjiang University of Chinese MedicineSchool of basic Medicine, Heilongjiang University of Chinese MedicineSchool of basic Medicine, Heilongjiang University of Chinese MedicineSchool of basic Medicine, Heilongjiang University of Chinese MedicineSchool of basic Medicine, Heilongjiang University of Chinese MedicineAbstract This study employs structural bioinformatics approaches to identify and evaluate potential drug targets within the Hepatitis C virus (HCV) proteome. Through integration of homology modeling, molecular docking, and molecular dynamics simulations, we analyzed the structural features and druggability of key HCV proteins. The research focused on predicting binding sites, evaluating protein-ligand interactions, and assessing the therapeutic potential of identified targets. Our findings revealed promising drug targets including the NS3 protease, NS5B polymerase, core protein, and NS5A, with detailed characterization of their binding pockets and interaction patterns. The study provides structural insights for rational drug design against HCV and demonstrates the utility of computational approaches in antiviral drug discovery. While experimental validation is needed, these results contribute to the development of novel anti-HCV therapeutics and highlight potential strategies for targeted intervention.https://doi.org/10.1038/s41598-025-12563-wHepatitis C virusStructural bioinformaticsDrug targetsMolecular dockingAntiviral therapeuticsProtein modeling |
| spellingShingle | Miao Qu Mingzhu Gao Xisheng Sang Miao Yu Zihe Guan Weizhi Chang Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis Scientific Reports Hepatitis C virus Structural bioinformatics Drug targets Molecular docking Antiviral therapeutics Protein modeling |
| title | Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis |
| title_full | Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis |
| title_fullStr | Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis |
| title_full_unstemmed | Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis |
| title_short | Structural bioinformatics approaches for predicting novel drug targets in hepatitis C virus proteins: a comprehensive analysis |
| title_sort | structural bioinformatics approaches for predicting novel drug targets in hepatitis c virus proteins a comprehensive analysis |
| topic | Hepatitis C virus Structural bioinformatics Drug targets Molecular docking Antiviral therapeutics Protein modeling |
| url | https://doi.org/10.1038/s41598-025-12563-w |
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