Abstract
Summary: Missense mutations that change protein stability are strongly associated with human genetic disease. With the recent availability of predicted structures for all human proteins generated using the AlphaFold2 prediction model, genome-wide assessment of the stability effects of genetic variation can, for the first time, be easily performed. This facilitates the interrogation of personal genetic variation for potentially pathogenic effects through the application of stability metrics. Here, we present a novel tool to prioritize variants predicted to cause strong instability in essential proteins. We show that by filtering by ΔΔG values and then prioritizing by StabilitySort Z-scores, we are able to more accurately discriminate pathogenic, protein-destabilizing mutations from population variation, compared with other mutation effect predictors.
Original language | English |
---|---|
Pages (from-to) | 4220-4222 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 38 |
Issue number | 17 |
DOIs | |
Publication status | Published - 1 Sept 2022 |