Unlocking the antiviral arsenal: Computational exploration of Langya virus (L, C, V, W) through phylogenetic analysis and molecular modeling

Objectives: In response to the ongoing COVID-19 pandemic and the resurgence of the Langya virus (LayV) in Eastern China, there is an urgent need for novel antiviral treatments. Given the limited research available on LayV, this study aimed to explore its evolutionary relationships and construct accurate three-dimensional (3D) models of key viral proteins, which are essential for understanding the virus’s mechanisms and vulnerabilities. Materials and Methods: Computational approaches were employed to examine the evolutionary relationships of LayV using Molecular Evolutionary Genetics Analysis (MEGA). To build reliable 3D protein structures of the viral proteins C, L, W, and V, SwissModel and Faster AlphaFold (AF) were utilised. Model validation was conducted in PROCHECK, PROSA, Errat, Verify 3D, and Prove. Additionally, binding site analysis was carried out using various platforms such as Computed Atlas of Surface Topography of Proteins (CASTp), PHYRE2, PrankWeb, and SCFBio to ensure the robust identification of key interaction sites. Results: The phylogenetic analysis revealed that LayV is closely related to the Henipavirus genus. The structural models generated through SwissModel for the C, L, and W proteins showed high accuracy, with 93.2%, 89.4%, and 87.5% of residues residing in favoured regions, respectively. The AF model of the V protein exhibited optimal structural validation, with 82.0% of residues in favoured regions. Binding site analysis identified key interaction regions essential for targeted drug design. Conclusion: This comprehensive study highlighted the close evolutionary relationship between LayV and Henipaviruses and validated the structural models of key LayV proteins, offering a foundation for future antiviral drug design. The robust computational analysis and structural modelling provide a critical framework for selective drug development, contributing to the strategic fight against LayV.

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Publication Details

Journal
American Journal of Biopharmacy and Pharmaceutical Sciences
Published
2024-12-12
DOI
https://doi.org/10.25259/ajbps_13_2024
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
0.00
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article

Unlocking the antiviral arsenal: Computational exploration of Langya virus (L, C, V, W) through phylogenetic analysis and molecular modeling

Sukesh Kalva, Venu Paritala, Rajashekhar Reddy Shagamreddy
American Journal of Biopharmacy and Pharmaceutical Sciences
Mosquito-borne diseases and control
article

Unlocking the antiviral arsenal: Computational exploration of Langya virus (L, C, V, W) through phylogenetic analysis and molecular modeling

Sukesh Kalva, Venu Paritala, Rajashekhar Reddy Shagamreddy
article en

Abstract

Objectives: In response to the ongoing COVID-19 pandemic and the resurgence of the Langya virus (LayV) in Eastern China, there is an urgent need for novel antiviral treatments. Given the limited research available on LayV, this study aimed to explore its evolutionary relationships and construct accurate three-dimensional (3D) models of key viral proteins, which are essential for understanding the virus’s mechanisms and vulnerabilities. Materials and Methods: Computational approaches were employed to examine the evolutionary relationships of LayV using Molecular Evolutionary Genetics Analysis (MEGA). To build reliable 3D protein structures of the viral proteins C, L, W, and V, SwissModel and Faster AlphaFold (AF) were utilised. Model validation was conducted in PROCHECK, PROSA, Errat, Verify 3D, and Prove. Additionally, binding site analysis was carried out using various platforms such as Computed Atlas of Surface Topography of Proteins (CASTp), PHYRE2, PrankWeb, and SCFBio to ensure the robust identification of key interaction sites. Results: The phylogenetic analysis revealed that LayV is closely related to the Henipavirus genus. The structural models generated through SwissModel for the C, L, and W proteins showed high accuracy, with 93.2%, 89.4%, and 87.5% of residues residing in favoured regions, respectively. The AF model of the V protein exhibited optimal structural validation, with 82.0% of residues in favoured regions. Binding site analysis identified key interaction regions essential for targeted drug design. Conclusion: This comprehensive study highlighted the close evolutionary relationship between LayV and Henipaviruses and validated the structural models of key LayV proteins, offering a foundation for future antiviral drug design. The robust computational analysis and structural modelling provide a critical framework for selective drug development, contributing to the strategic fight against LayV.

American Journal of Biopharmacy and Pharmaceutical SciencesVol. 4
Vignan's Foundation for Science, Technology & Research (IN), Grand Valley State University (US)
Good health and well-being
Openalex Percentile: Top 65%
Mosquito-borne diseases and control
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