Computational insights into PKCθ non-synonymous SNPs: from structural changes to functional implications

Single-nucleotide polymorphisms (SNPs) play a critical role in individual diversity, genome evolution, and susceptibility to diseases such as cancer and diabetes. This study focuses on the PRKCQ gene, encoding protein kinase C theta (PKCθ), a serine/threonine kinase belonging to the PKC family, involved in immune response and cancer progression. Pathogenicity assessment using multiple bioinformatic tools identified six highly pathogenic non-synonymous SNPs (nsSNPs), all predicted to be oncogenic (rs1838691533 R6W, rs145984477 P27L, rs1248923790 C29Y, rs1837738907 R145C, rs1837738573 R146W, rs1403981107 L495P). Structural predictions and domain analyses identified crucial functional regions in PKCθ, with specific variants located in domains essential for membrane binding and catalytic activity. Conservation profiling highlighted the evolutionary significance of these residues, indicating their critical roles in protein function. Stability analysis of selected nsSNPs demonstrated that most variations decrease protein stability, confirmed by various computational tools. Molecular dynamics (MD) simulations further showed that these variants significantly alter PKCθ’s conformation and stability, impacting its function. These findings underscore the importance of PKCθ in oncogenic signaling and highlight the potential for targeted therapies and personalised medicine approaches to address PRKCQ-associated diseases.