Abstract
Characterising the consequences of naturally occurring nucleotide changes is a powerful approach to the identification of amino acid residues that are critical to protein function. While, numerous computational tools have been developed to predict variant effects in-silico, these have variable accuracy and rarely take into account protein three-dimensional structures.
Here we propose to combine experimental and computational methods to identify the amino acid substitutions that are more likely to de-stabilize the structure of multi-protein complexes. As the discrimination between benign and deleterious changes can be especially challenging for immune genes, the project will focus on variants that affect inflammatory proteins.
References
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