Stefan J. Hamill

The structure of a PKD domain from polycystin‐1: implications for polycystic kidney disease

Most cases of autosomal dominant polycystic kidney disease (ADPKD) are the result of mutations in the PKD1 gene. The PKD1 gene codes for a large cell‐surface glycoprotein, polycystin‐1, of unknown function, which, based on its predicted domain structure, may be involved in protein–protein and protein–carbohydrate interactions. Approximately 30% of polycystin‐1 consists of 16 copies of a novel protein module called the PKD domain. Here we show that this domain has a β‐sandwich fold. Although this fold is common to a number of cell‐surface modules, the PKD domain represents a distinct protein family. The tenth PKD domain of human and Fugu polycystin‐1 show extensive conservation of surface residues suggesting that this region could be a ligand‐binding site. This structure will allow the likely effects of missense mutations in a large part of the PKD1 gene to be determined.

Using Model Proteins to Quantify the Effects of Pathogenic Mutations in Ig-like Proteins

It has proved impossible to purify some proteins implicated in disease in sufficient quantities to allow a biophysical characterization of the effect of pathogenic mutations. To overcome this problem we have analyzed 37 different disease-causing mutations located in the L1 and IL2Rγ proteins in well characterized related model proteins in which mutations that are identical or equivalent to pathogenic mutations were introduced. We show that data from these models are consistent and that changes in stability observed can be correlated to severity of disease, to correct trafficking within the cell and to in vitro ligand binding studies. Interestingly, we find that any mutations that cause a loss of stability of more than 2 kcal/mol are severely debilitating, even though some model proteins with these mutations can be easily expressed and analyzed. Furthermore we show that the severity of mutation can be predicted by a ΔΔGevolution scale, a measure of conservation. Our results demonstrate that model proteins can be used to analyze disease-causing mutations when wild-type proteins are not stable enough to carry mutations for biophysical analysis.