Investigation of Missense Mutations in the SHBG Gene: Bioinformatic Analysis and Pathogenesis Prediction in binding and regulating the bioavailability of sex hormones

Sex Hormone-Binding Globulin (SHBG) is a glycoprotein produced by the SHBG gene, which plays an essential role in binding and regulating the availability of sex hormones, such as testosterone and estradiol. Alterations in the SHBG gene can disrupt its function and lead to various health issues. In this study, we identified ten missense single nucleotide polymorphisms (SNPs) in the SHBG gene using the NCBI SNP database: rs۱۴۷۴۴۱۷۷۹۶ (Gly۲۳۰Arg), rs۱۴۷۳۸۲۴۳۷۵ (Leu۴۲Pro), rs۱۴۷۱۵۸۱۷۱۷ (Gly۲۴۵Glu), rs۱۴۶۴۷۵۳۷۲۲ (Pro۱۷۱Ala), rs۶۲۵۸ (Pro۱۸۵Gln), rs۱۴۲۶۹۳۱۷۰ (Thr۳۹۸Asn), rs۱۴۶۷۷۹۳۵۵ (Gly۲۲۴Glu), rs۱۴۷۴۵۵۴۹۸۵ (Val۳۱۵Met), rs۱۴۴۸۶۴۹۲۱۶ (Ser۲۶۶Arg), and rs۱۴۲۷۵۵۵۶۲۱ (Leu۱۷Met). Several bioinformatics tools, including PolyPhen۲, I-Mutant, SIFT, HOPE, Expasy, and NetSurf P ۳.۰, were employed to assess the structural and functional impacts of the analyzed single nucleotide polymorphisms (SNPs). PolyPhen۲ predictions indicated that all ten SNPs are potentially damaging, with scores exceeding ۰.۹۵, which suggests a high likelihood of pathogenicity. I-Mutant analyses consistently showed a decrease in protein stability for these variants, reinforcing the hypothesis that they may have deleterious effects. SIFT results confirmed that these SNPs are likely to disrupt the normal function of the SHBG protein. Structural modeling using HOPE and Expasy revealed significant changes in the protein's conformation, interaction patterns, and hydrophobic properties. Furthermore, NetSurfP ۳.۰ results indicated altered surface accessibility and changes in secondary structural elements, which could impact the protein's interactions with ligands and other biomolecules. While all analyzed SNPs are predicted to be pathogenic and detrimental to the stability and function of SHBG, their specific impacts differ. These variations underscore the complexity of structural and functional disruptions caused by SNPs, highlighting the importance of experimental validation. Laboratory studies are necessary to confirm these computational predictions and to elucidate the molecular mechanisms through which these SNPs affect SHBG and their potential role in disease. In conclusion, this bioinformatics-based study suggests that these missense SNPs in the SHBG gene may contribute to pathogenic outcomes by disrupting the protein's stability and functionality. However, further experimental validation is required to confirm the accuracy of these predictions and their clinical significance.

کلیدواژه ها:

SHBG ، Missense SNPs ، bioinformatics analysis ، pathogenicity ، polycystic ovary