Investigation Of Variants Of Uncertain Significance In Clptm1l

This study aimed to evaluate the pathogenicity of 33 variants of uncertain significance (VUS) in CLPTM1L, a gene involved in apoptosis regulation and oncogenic transformation, with genetic variations linked to oral cancer risk. We employed computational tools to assess the pathogenicity of 33 variants of uncertain significance (VUS) in CLPTM1L. Structural modeling using AlphaFold and root mean square deviation (RMSD) analysis quantified conformational changes in mutant proteins, with an independent-samples t-test used for statistical evaluation. AlphaMissense, CADD, and SNPs&GO classified VUS, while PIK3CA served as a benchmark due to its relatively well-classified variants. Molecular docking with AutoDock analyzed the interaction between PIK3CA and Copanlisib. Four mutations (F523S, F109C, D499V, L421P) were classified as likely pathogenic, exhibiting high CADD scores (≥20) and disease associations in SNPs&GO. AlphaMissense predictions were consistent with these findings. Structural analysis showed no significant conformational deviations (P > 0.05), but molecular docking revealed altered inhibitor interactions, particularly in hydrogen bonding patterns, while maintaining strong binding affinities. Our study demonstrated that AI-driven computational approaches effectively classify VUS in CLPTM1L, providing insights into their potential oncogenic relevance. Identifying pathogenic mutations can support precision medicine by enabling targeted therapies and early diagnosis, reinforcing the clinical significance of VUS classification in oral cancer.