Computational Profiling and Pathogenicity Assessment of VHL Missense Mutations

Abstract

Mutations in the VHL tumor suppressor gene promote tumorigenesis by stabilizing HIF-1. In this study, we investigated the functional impact of VHL missense mutations using AlphaMissense pathogenicity scores, protein stability simulations, and molecular dynamics. AlphaMissense identified high pathogenicity scores for residues 60-200, including the {beta}-domain and HIF-binding domain, suggesting these regions are critical for VHL's tumor suppressor function. We categorized the mutations into two groups: those that primarily destabilize protein folding and those that likely disrupt VHL-HIF-1 binding. FoldX stability simulations revealed high {Delta}{Delta}G values for both groups, with proline substitutions exerting significant structural stress. Structural modeling confirmed that these mutations disrupt secondary structures, particularly {beta}-sheets. Molecular dynamics simulations showed that the VHL monomer is flexible and unstable in several regions, whereas the VHL-HIF complex, particularly the HIF-binding domain, exhibits enhanced stability. Mutational scanning revealed that bulky amino acid substitutions, such as tryptophan, cause notable destabilization. Interestingly, some mutations predicted to be structurally stable were still classified as pathogenic by AlphaMissense and validated in the literature, suggesting that pathogenicity may arise from subtle functional impairments rather than just structural instability. These findings underscore the value of combining machine learning, structural simulations, and experimental data to predict and interpret the pathogenicity of VHL mutations.