In silico mutational scanning to understand and predict protein function and genetic disease
Supervisor: Dr Joe Marsh
Recent advances in machine learning and the development of high-throughput deep mutational scanning strategies are revolutionising our ability to interpret human genetic variation. This project will use state-of-the-art variant effect predictors and protein structural models to perform in silico saturation mutagenesis on a variety of proteins implicated in human genetic disease. This will enable us to better understand protein function and its relationship to disease, and establish optimal strategies for computationally predicting the effects and molecular disease mechanisms of novel variants, thus ultimately improving the diagnosis and treatment of human genetic disorders.
Gerasimavicius L, Livesey BJ & Marsh JA (2022) Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure. Nature Communications 13:3895