Introduction: Wilson's disease (WD) is an autosomal recessive hereditary disorder caused by mutations in the ATP7B gene, which impair copper homeostasis. The clinical heterogeneity observed in patients suggests the involvement of modifier genes influencing phenotypic expression. Objective: We aimed to characterize the structural and functional properties of genes associated with WD through a bioinformatic approach, aiming to identify relevant molecular patterns and potential modifier genes. Methods: Genes related to WD were retrieved from the MalaCards database. Structural annotation was performed using the UCSC Genome Browser (GRCh38/hg38), including for the gene architecture, regulatory elements, repeat content, and evolutionary conservation. The data were statistically processed using Python scripts, and functional enrichment analyses (ToppGene) and protein–protein interaction analyses (STRING) were conducted. The genes were grouped based on patterns of functional convergence and structural divergence. Results: A total of 21 genes were identified with significant structural divergence in terms of their exon number, transcript variants, and conservation, yet they exhibited convergent biological functions related to key processes such as the homeostasis of metals, particularly copper. Subgroups were observed with compact gene architectures and high conservation, as well as others with greater structural complexity and lower conservation. Notable genes included COMMD1, ABCC2, HFE, ATP7A, SLC11A2, SLC31A2, and MT1E, some of which have previously been described as potential modifiers in WD. Conclusions: These findings support the existence of structurally divergent yet functionally convergent genes in the pathophysiology of WD. Their identification highlights their potential as candidates for use in functional studies aimed at understanding clinical variability and developing predictive models of this disease.