Computational stability analysis suggests binding-independent destabilization in pathogenic FBXO11 variants

Area of Science:

• Genetics
• Biochemistry
• Computational Biology

Background:

• FBXO11 is part of an SCF E3 ubiquitin ligase complex, crucial for substrate ubiquitination and degradation.
• Pathogenic FBXO11 variants are linked to neurodevelopmental disorders, but the exact mechanisms remain unclear, as some variants retain normal SKP1 binding.

Purpose of the Study:

• To investigate the role of protein destabilization versus altered SKP1 binding in FBXO11-associated neurodevelopmental disorders.
• To evaluate the predictive power of computational stability predictions for missense variants in FBXO11.

Main Methods:

• Integrated multi-conformational AlphaFold3 models with FoldX and Rosetta stability predictions to assess 44 FBXO11 missense variants.
• Benchmarked physics-based ΔΔG predictions against existing tools like AlphaMissense, REVEL, and CADD.
• Performed exploratory molecular dynamics simulations to analyze variant-induced structural changes.

Main Results:

• Pathogenic FBXO11 variants showed significantly greater predicted destabilization compared to benign variants using both FoldX and Rosetta.
• Computational predictions accurately identified destabilization in pathogenic variants, even those with experimentally validated normal SKP1 binding.
• Physics-based ΔΔG predictions offered complementary mechanistic insights compared to existing variant prediction tools.

Conclusions:

• Protein destabilization, independent of SKP1 binding, is a likely mechanism underlying FBXO11-associated pathogenesis.
• Computational stability predictions are valuable tools for understanding the impact of genetic variants.
• Further computational and experimental validation is warranted to fully elucidate the role of destabilization in FBXO11-related diseases.