Article ; Online: A simulation-based approach to target Zika virus RNA-dependent RNA polymerase with marine compounds for antiviral development.
Journal of biomolecular structure & dynamics
2024 , Page(s) 1–11
Abstract: Despite significant efforts, currently, there is no particular drug available to treat Zika virus (ZIKV) infection, highlighting the urgent need for effective therapeutic interventions. To identify putative inhibitors of the ZIKV RdRp protein's RNA ... ...
| Abstract | Despite significant efforts, currently, there is no particular drug available to treat Zika virus (ZIKV) infection, highlighting the urgent need for effective therapeutic interventions. To identify putative inhibitors of the ZIKV RdRp protein's RNA binding function, the present study applied an extensive in-silico drug discovery methodology. The initial phase involved virtual screening using Lipinski's rule of five as a filter, ensuring the selection of molecules with favorable pharmacokinetic properties. This process yielded 238 compounds with promising docking scores, ranging from -6.0 to -7.48 kcal/mol, indicative of their potential binding affinity to the ZIKV RdRp. To refine the selection, these compounds underwent a re-docking process, comparing their binding energies with a reference molecule known for its inhibitory action against RdRp. Remarkably, five compounds, labeled CMNPD30598, CMNPD27464, CMNPD25971, CMNPD27444, and CMNPD16599, demonstrated superior re-docking energies compared to the reference, suggesting a stronger interaction with the RdRp allosteric site. Subsequent molecular dynamics (MD) simulations provided insights into the stability of these complexes over time, reinforcing their potential as RdRp inhibitors. Additionally, the calculation of free binding energies and principal component analysis (PCA) of the free energy landscape offered a deeper understanding of the binding dynamics and energetics. This study not only highlights the utility of marine fungi compounds in antiviral drug discovery but also showcases the power of computational tools in identifying novel therapeutics. The identified compounds represent promising candidates for further experimental validation and development as ZIKV RdRp inhibitors.Communicated by Ramaswamy H. Sarma. |
|---|---|
| Language | English |
| Publishing date | 2024-02-28 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 49157-3 |
| ISSN | 1538-0254 ; 0739-1102 |
| ISSN (online) | 1538-0254 |
| ISSN | 0739-1102 |
| DOI | 10.1080/07391102.2024.2322620 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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