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

Area of Science:

• Genetics and Molecular Biology
• Bioinformatics
• Cancer Research

Background:

• Single-nucleotide polymorphisms (SNPs) are key to individual genetic variation, evolution, and disease susceptibility, including cancer and diabetes.
• The PRKCQ gene encodes protein kinase C theta (PKCθ), a crucial enzyme in immune responses and cancer development.

Purpose of the Study:

• To identify and characterize pathogenic non-synonymous SNPs (nsSNPs) in the PRKCQ gene.
• To assess the impact of these nsSNPs on PKCθ protein structure, stability, and function.
• To explore the implications of these findings for PRKCQ-associated diseases and personalized medicine.

Main Methods:

• Utilized multiple bioinformatics tools for pathogenicity assessment of nsSNPs.
• Performed structural predictions, domain analysis, and conservation profiling of PKCθ.
• Conducted stability analyses and molecular dynamics (MD) simulations for selected nsSNPs.

Main Results:

• Identified six highly pathogenic and oncogenic nsSNPs in PRKCQ (rs1838691533 R6W, rs145984477 P27L, rs1248923790 C29Y, rs1837738907 R145C, rs1837738573 R146W, rs1403981107 L495P).
• Found variants located in critical functional domains of PKCθ, affecting membrane binding and catalytic activity.
• Demonstrated that most nsSNPs decrease protein stability and significantly alter PKCθ conformation and dynamics.

Conclusions:

• Pathogenic nsSNPs in PRKCQ can critically impact PKCθ function, contributing to oncogenic signaling.
• These findings highlight the role of PRKCQ in cancer and suggest potential for targeted therapies.
• The study supports personalized medicine approaches for diseases associated with PRKCQ variations.