Lesch-Nyhan disease (LND) is a neurogenetic disorder characterized by hyperuricemia and a characteristic neurobehavioral syndrome. Like most other neurogenetic diseases, the pathogenesis of LND reflects a multi- step process leading from the primary genetic defect, through secondary biochemical changes, and then tertiary physiologic and anatomical changes which ultimately lead to the clinical phenotype. LND is caused by mutations in the gene encoding hypoxanthine-guanine phosphoribosyltransferase (HGprt), an enzyme that plays a well-characterized role in purine metabolism. Specifically, it has dual functions in the salvage pathways, serving to recycle both hypoxanthine and guanine. Although the loss of HGprt enzyme activity is the primary biochemical defect, multiple additional secondary biochemical changes have also been identified. Currently, we have a very limited understanding of which of these biochemical changes is most relevant to downstream events in the pathophysiological cascade and how these changes produce the neurobehavioral syndrome. The studies of this proposal are aimed at separating the 2 functions of HGprt, hypoxanthine recycling (Hprt) and guanine recycling (Gprt), to determine which is most important for pathogenesis. Our working hypothesis is that the pathogenesis of the clinical phenotype depends predominantly on 1 or the other function.
AIM 1 is devoted to computer graphic modeling of a large database of HGprt mutations associated with human disease to predict clinically relevant mutants that may be selective recyclers of hypoxanthine or guanine.
AIM 2 is devoted to empirical verification of the results of computer graphic modeling via direct biochemical assay of the informative mutants identified in AIM 1. The results of these experiments will provide a major advance in our understanding of the pathogenesis of the neurobehavioral features of LND by determining which of the 2 main biochemical functions of HGprt is most relevant for pathogenesis. The significance of the results is not limited to LND, as this novel application of computer graphic modeling could also be used to elucidate key steps in the pathogenesis of other disorders associated with proteins that have multiple substrates or disorders where the relationship between ligand-protein interactions and clinical phenotype is not well understood. ? ? ?
