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Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction
Published on: November 1, 2018
In-silico Identification of Novel Inhibitors Targeting Dengue Virus Serotype 3 RNA-Dependent RNA Polymerase
Shailaja Mallya1, Raghuvir R S Pissurlenkar2
1Department of Pharmacology, Goa College of Pharmacy, Panaji, Goa University, Goa 403001, India.
Introduction:
Dengue infection, caused by four serotypes of the dengue virus (DENV), poses a significant global health threat, with millions of cases reported annually. RNAdependent RNA polymerase (RdRp) is an essential viral enzyme involved in the replication cycle and is a promising target for antiviral drug development. In the present study, computational methods were employed to identify novel compounds with potential inhibitory activity against DENV serotype 3 RdRp.
Methods:
Molecular docking-based virtual screening approaches were used to screen a diverse library of small molecules against the three-dimensional structure of DENV-3 RdRp. Furthermore, pharmacokinetic and toxicity predictions were utilized to prioritize compounds with favorable drug-like properties. Subsequently, molecular dynamics simulation studies were performed to assess the stability and binding affinity of the predicted inhibitors.
Results:
The computational studies yielded three promising DENV serotype 3 RNA-dependent RNA polymerase inhibitors, with docking scores ranging from -8.89 to -8.19 kcal/mol. MD simulations over 100 ns demonstrated stable protein-ligand complexes, with backbone RMSDs varying from 0.77 to 1.87 Å.
Discussions:
Comprehensive interaction analysis revealed that Z248 and Z982 engaged key catalytic residues Arg729 and Arg737 within the palm domain, while Z389 exhibited hydrophobic stabilization through interaction with Trp795. These residues are critical for enzymatic activity, and their engagement highlights the mechanistic relevance of the identified compounds. The dynamic stability of the RdRp-ligand complexes was further validated through 100 ns molecular dynamics simulations, with both protein backbone and ligand RMSDs remaining within acceptable limits.
Conclusions:
The identified inhibitors, obtained from exhaustive computational studies, represent promising candidates for further experimental validation and optimization as potential antiviral agents for the treatment of DENV-3 infections.
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