Integrative In Silico Analysis to Identify Functional and Structural Impacts of nsSNPs on Programmed Cell Death Protein 1 (PD-1) Protein and UTRs: Potential Biomarkers for Cancer Susceptibility.

Programmed cell death protein 1 (PD-1), encoded by the gene, is critical in immune checkpoint regulation and cancer immune evasion. Variants in may alter its function, impacting cancer susceptibility and disease progression. This study evaluates the structural, functional, and regulatory impacts of non-synonymous single-nucleotide polymorphisms (nsSNPs) in the gene, focusing on their pathogenic and oncogenic roles. Computational tools, including PredictSNP1.0, I-Mutant2.0, MUpro, HOPE, MutPred2, Cscape, Cscape-Somatic, GEPIA2, cBioPortal, and STRING, were used to analyze 695 nsSNPs in the PD1 protein. The analysis covered structural impacts, stability changes, regulatory effects, and oncogenic potential, focusing on conserved domains and protein-ligand interactions. The analysis identified 84 deleterious variants, with 45 mapped to conserved regions like the Ig V-set domain essential for ligand-binding interactions. Stability analyses identified 78 destabilizing variants with significant protein instability (ΔΔG values). Ten nsSNPs were identified as potential cancer drivers. Expression profiling showed differential expression in tumor versus normal tissues, correlating with improved survival in skin melanoma but limited value in ovarian cancer. Regulatory SNPs disrupted miRNA-binding sites and transcriptional regulation, affecting expression. STRING analysis revealed key PD-1 protein partners within immune pathways, including PD-L1 and PD-L2. This study highlights the significance of nsSNPs as potential biomarkers for cancer susceptibility, advancing the understanding of PD-1 regulation. Experimental validation and multi-omics integration are crucial to refine these findings and enhance theraputic strategies.