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Updated: May 20, 2025

Quantifying Human Norovirus Virus-like Particles Binding to Commensal Bacteria Using Flow Cytometry
Published on: April 29, 2020
Exploring deleterious non-synonymous SNPs in FUT2 gene, and implications for norovirus susceptibility and gut
Muhammad Waleed Iqbal1, Muneer Ahmad2, Muhammad Shahab1
1State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Abstract:
Fucosyltransferase 2 (FUT2) gene has been extensively reported to play its role in potential gut microbiota changes and norovirus susceptibility. The normal activity of FUT2 has been found to be disrupted by non-synonymous single nucleotide polymorphisms (nsSNPs) in its gene. To explore the possible mutational changes and their deleterious effects, we employed state-of-the-art computational strategies. Firstly, nine widely-used bioinformatics tools were utilized for initial screening of possibly deleterious nsSNPs. Subsequently, the structural and functional effects of screened nsSNPs on FUT2 were evaluated by utilizing relevant computational tools. Following this, the two shortlisted nsSNPs, including G149S (rs200543547) and V196G (rs367923363), were further validated by their molecular docking with norovirus capsid protein, VP1. As compared to wild-type, the higher stability and lower binding energy scores of the both the mutants indicated their stable binding with VP1, which ultimately leads to norovirus implications. These docking results were further verified by a comprehensive computational approach, molecular dynamic simulation, which gave results in the form of lower RMSD, RMSF, RoG, and hydrogen bond values of both the mutants, depicted in relevant graphs. Overall, this research explores and validated the two FUT2 nsSNPs (G146S and V196G), which may possibly linked with the norovirus susceptibility and gut microbiota changes. Moreover, our findings highlights the value of computational strategies in mutational analysis and welcomes any further experimental validation.
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