Background: Dectin-1 is a pattern recognition receptor that recognizes pathogenic
fungi via carbohydrate moiety present on the cell wall. Single nucleotide polymorphisms
in dectin-1 gene in an individual have been implicated in susceptibility to invasive
infections in immunocompromised or immunocompetant host.
Objective: We sought to analyze the deleterious nsSNP in dectin-1 gene for their susceptibility
against fungal pathogens
Methods: SNPs were retrieved from dbSNP database. Five in-silico algorithms (SIFT,
PhD-SNP, SNAP, PolyPhen-2 and MAPP) were used to determine the functional consequences
of non-synonymous SNPs. Conservation profiling of dectin-1 receptor protein
was carried out using ConSurf. The three-dimensional (3D) structure of wild-type C-type
lectin domain of dectin-1 protein was modeled using Phyre2 version-2, a web-based
server. The protein stability was characterized using I-mutant tool.
Results: A total of 91 non-synonymous SNPs were identified. Seven high-risk nonsynonymous
SNPs in dectin-1 receptor were observed using five in-silico algorithms.
Domain analysis resulted in the identification of C-type lectin domain. 3D structure modeling
of C-type lectin domain as well as for seven variants of nsSNP in C-type lectin domain
was carried out for determining their effect on structure-function in protein. Furthermore,
I-Mutant revealed that the protein stability decreased which destabilized the
amino acid interactions. The highest alteration in protein structures were observed in
I223S (rs16910527), I158T (rs138005591) and D159G (rs 758623997) variants.
Conclusion: We propose that these non-synonymous SNPs in dectin-1 receptor encoding
gene could be considered for risk assessment against fungal infections.