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Background <p>SNPs (Single-nucleotide polymorphisms) are alterations in a single base pair within the genome that appear in at least 1% of the population, making them the most prevalent type of genetic variation among humans. These genetic differences can affect gene function and regulation, thereby influencing individual variations in disease susceptibility, including complex conditions such as PCOS (Polycystic Ovary Syndrome). PCOS is a common endocrine disorder. The relationship between PCOS and <i>FSHR </i>(<i>Follicle Stimulating Hormone Receptor</i>) has attracted much research attention because FSH (Follicle Stimulating Hormone) has significant biological functions. <i>FSHR</i> regulates FSH levels, and aberrant <i>FSHR</i> expression affects folliculogenesis. Although <i>FSHR</i> and its protein have been extensively studied, variants of this gene must be methodically analyzed.</p> Results <p>In silico analysis of 743 missense SNPs in the <i>FSHR</i> gene identified 18 variants predicted to be deleterious by multiple computational tools. Structural analysis revealed that 15 of these variants likely reduced the protein stability. Evolutionary conservation analysis highlighted 12 variants in highly conserved regions, suggesting potential functional significance. Protein modeling and docking simulations indicated that Bonducellin exhibited stronger binding affinity to mutant FSHR than metformin, with more favorable interactions in the receptor-binding pocket. These findings provide insights into the potentially impactful FSHR variants and identify promising compounds for further investigation.</p> Conclusion <p>This study prioritized five FSHR nsSNPs—P45L, A189V, D224V, L535P, and L611P, based on in silico predictions that highlight their potential functional significance. These variants are important for further exploration as they could serve as biomarkers or therapeutic targets in PCOS. Furthermore, molecular docking results suggest that Bonducellin, a natural compound derived from Caesalpinia bonducella, may modulate FSHR activity. While bioinformatics is a valuable tool for identifying genetic variants and therapeutic prospects, the findings of this study need experimental and clinical validation before they can be applied in clinical practice.</p>

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Decoding the FSHR gene: a multi-tool computational approach to SNPs with potential application in PCOS

  • 期刊论文

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  • 发表日期：

    2025年8月6日

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  • Dolly J. Patel,
  • Kinnari N. Mistry

摘要

Background

SNPs (Single-nucleotide polymorphisms) are alterations in a single base pair within the genome that appear in at least 1% of the population, making them the most prevalent type of genetic variation among humans. These genetic differences can affect gene function and regulation, thereby influencing individual variations in disease susceptibility, including complex conditions such as PCOS (Polycystic Ovary Syndrome). PCOS is a common endocrine disorder. The relationship between PCOS and FSHR (Follicle Stimulating Hormone Receptor) has attracted much research attention because FSH (Follicle Stimulating Hormone) has significant biological functions. FSHR regulates FSH levels, and aberrant FSHR expression affects folliculogenesis. Although FSHR and its protein have been extensively studied, variants of this gene must be methodically analyzed.

Results

In silico analysis of 743 missense SNPs in the FSHR gene identified 18 variants predicted to be deleterious by multiple computational tools. Structural analysis revealed that 15 of these variants likely reduced the protein stability. Evolutionary conservation analysis highlighted 12 variants in highly conserved regions, suggesting potential functional significance. Protein modeling and docking simulations indicated that Bonducellin exhibited stronger binding affinity to mutant FSHR than metformin, with more favorable interactions in the receptor-binding pocket. These findings provide insights into the potentially impactful FSHR variants and identify promising compounds for further investigation.

Conclusion

This study prioritized five FSHR nsSNPs—P45L, A189V, D224V, L535P, and L611P, based on in silico predictions that highlight their potential functional significance. These variants are important for further exploration as they could serve as biomarkers or therapeutic targets in PCOS. Furthermore, molecular docking results suggest that Bonducellin, a natural compound derived from Caesalpinia bonducella, may modulate FSHR activity. While bioinformatics is a valuable tool for identifying genetic variants and therapeutic prospects, the findings of this study need experimental and clinical validation before they can be applied in clinical practice.