A single physical number measuring protein stability can accurately predict how sick a patient will be across over 100 different genetic diseases.
Doctors traditionally struggled to predict the severity of intermediate filament disorders because each mutation seemed unique. A simple thermodynamic metric called folding free energy has now emerged as a universal predictor of clinical outcomes. Higher levels of protein destabilization correlate directly with more aggressive symptoms in patients. This rule applies regardless of which specific protein or organ system the mutation affects. Having a mathematical way to forecast disease progression allows for more personalized treatment plans and better clinical trials.
Folding free energy as a unifying predictor of intermediate filament disease severity
research_square · rs-9257849
Abstract Background: Mutations in intermediate filament genes cause over 100 human diseases, yet predicting clinical severity from genotype remains unreliable due to phenotypic variability and the prevalence of variants of uncertain significance. Methods: FoldX folding free energy changes (ΔΔG) were calculated on AlphaFold2-predicted structures for 323 pathogenic missense mutations across four intermediate filament genes: DES (n = 96), LMNA (n = 94), KRT5 (n = 83), and KRT14 (n = 50). Prediction