In Silico Prioritization of High-Risk GSTO2 Missense Variants Using Consensus Pathogenicity Scoring, Static Structural Assessment, and Qualitative Docking

Glutathione S-transferase omega 2 (GSTO2) is implicated in oxidative stress management and detoxification, including reported dehydroascorbate reductase (DHAR)-related activity that supports cellular redox homeostasis. Because experimental functional data are unavailable for most GSTO2 missense variants, we performed an in silico prioritization study to rank nsSNPs for downstream validation rather than to infer causality or definitive functional effects. From 383 missense variants retrieved from dbSNP, we applied consensus pathogenicity screening (SIFT, PolyPhen-2, MutPred2, PANTHER, PhD-SNP, SNPs&GO, and CADD) to identify 14 high-priority candidates. We then used static structure-based assessment (template-based modeling with Phyre2/Swiss-Model, QMEAN component scores, HOPE and Missense3D structural alerts, and global alignment via TM-align) to contextualize predicted local perturbations within an overall conserved fold. Variants such as C32Y, L47R, and R156Q were prioritized because they map to chemically sensitive regions (including the catalytic cysteine environment) or introduce charge and packing changes in buried positions, and were associated with unfavorable model-quality components (e.g., torsion or all-atom terms). Docking of dehydroascorbic acid with AutoDock Vina provided qualitative support by comparing plausible poses and relative scores across variants; docking outputs were interpreted as hypothesis-generating rather than as evidence of gain- or a hypothesis for altered interaction patterns. Overall, this work delivers a ranked shortlist of GSTO2 variants with convergent computational risk signals and structure-based rationale to guide targeted biochemical and biophysical experiments.