Bioinformatics-driven identification of pathogenic missense nsSNPs in the human proto-oncogene SRC and cancer susceptibility.

SRC is a proto-oncogene that regulates cell proliferation and survival, and its dysregulation is commonly observed in diverse cancers. While SRC kinase dysregulation is well-established as a cancer driver, the functional consequences of its genetic variants, particularly non-synonymous single-nucleotide polymorphisms (nsSNPs) are not fully understood. Therefore, we employed an integrative computational approach to identify nsSNPs in SRC and analyze their impact on protein function and structure. Out of the 512 missense nsSNPs analyzed, 42 were predicted to be deleterious, with 12 likely to destabilize protein structure. Among these, three mutations, namely W151C (rs746439256), Y419N (rs2147125119), and P465S (rs1251532695), were particularly significant, causing substantial physicochemical changes. Molecular dynamics simulations revealed that these variations reduce protein stability and flexibility, resulting in conformational alterations. Docking study demonstrated that these mutations disrupt the binding interface residues of the SRC-FAK complex and affect dasatinib binding affinity. Additionally, gene expression analysis linked mutated SRC to dysregulation of cancer-related genes, especially in multiple myeloma and uterine cancer, and suggested reciprocal regulation by other mutated genes across malignancies. These findings highlight the oncogenic potential of SRC mutations and pave the way for future population-based studies exploring their role as diagnostic biomarkers, therapeutic targets, and modulators of drug response in personalized cancer treatment.