Comprehensive computational analysis of deleterious nsSNPs in PTEN gene for structural and functional insights

Single nucleotide polymorphisms (SNPs) are pivotal in understanding the genetic basis of complex disorders. Among them, nonsynonymous SNPs (nsSNPs) that alter amino acid sequences can significantly impact protein structure and function. This study focuses on analyzing deleterious nsSNPs in the tumor suppressor gene PTEN (Phosphatase and TENsin Homolog), which plays a central role in regulating the PI3K/Akt signaling pathway and tumorigenesis. Out of 43,855 SNPs in PTEN, 17 deleterious nsSNPs were identified using six computational tools. Protein stability analysis revealed that 15 variants reduce stability, potentially leading to functional impairment. Structural evaluations using HOPE and ConSurf classified mutations into buried structural residues disrupting protein integrity and exposed functional residues affecting molecular interactions. STRING database analysis highlighted PTEN as a central node in an intricate protein network, with deleterious mutations impairing critical interactions with partners such as PIK3CA, AKT1, and TP53. Secondary structure analysis revealed distinct structural deviations, particularly for G129E, which exhibited the most pronounced destabilization. Molecular dynamics simulations confirmed stability variations across mutants, with G129E exhibiting greater instability. This comprehensive analysis enhances understanding of PTEN nsSNP impacts, offering insights for therapeutic interventions and future experimental validation.