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Computational screening of pathogenic non-synonymous SNPs of the human TEX11 gene and their structural and functional consequences

Highlights•This study was undertaken to identify the deleteriouns nsSNPs of human TEX11 gene involved in male infertility•Detailed in silico analysis predicted seven nsSNPs of TEX11 as highly damaging (Y275C, L329P, F365C, W637R, L677R, L677P, and D734Y)•The predicted variants may prove useful for diagnostic purpose as genetic markers for male infertilityAbstractBackgroundInfertility is a reproductive health problem that affects 13%–18% of couples in the human population. Genetic factors contributing to infertility are a major cause of concern in couples seeking assisted reproductive techniques. Testis-expressed gene 11 (TEX11) is an X-linked gene responsible for a number of genetic infertility cases.ObjectivesScreening and identification of most deleterious non-synonymous SNPs (nsSNPs) in the human TEX11 gene associated with male infertility via various sequence and structural bioinformatics tools.MethodologyA systematic insilico analysis was performed using pathogenicity prediction tools including SIFT, PolyPhen, PROVEAN, PHDSNP, and MutPred to identify the damaging nsSNPs of TEX11. Protein stability changes were observed with I Mutant and MuPro. Molecular modeling and insilico site-directed mutagenesis approaches were used to build the wild type and mutant TEX11 protein models. Next through molecular dynamics simulations of TEX11WT and TEX11MT proteins were performed to assess important structural modifications and stability behavior.ResultsDetailed computational analysis predicted seven nsSNPs of TEX11 as highly damaging (Y275C, L329P, F365C, W637R, L677R, L677P, and D734Y) by all pathogenicity prediction tools. All these mutations showed to decrease protein stability and may contribute to dissociating the molecular interactions.ConclusionPresent comprehensive computational analysis confirms the pathogenicity of infertility associated TEX11 variants which could be used as a genetic diagnostic marker for future therapeutics measures.


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