Structural features of normal and mutant human lysosomal glycoside hydrolases deduced from bioinformatics analysis

Lysosomal storage diseases are due to inherited deficiencies in various enz ymes involved in basic metabolic processes. As with other genetic diseases, accurate structure data for these enzymatic proteins should help in better understanding the molecular effects of mutations identified in patients wi th the corresponding lysosomal diseases; however, no such three-dimensional (3D) structure data are available for many lysosomal enzymes, Thus, we her ein intend to illustrate for an audience of molecular geneticists how struc ture information can nonetheless be obtained via a bioinformatics approach in the case of five human lysosomal glycoside hydrolases. Indeed, using the two-dimensional hydrophobic cluster analysis method to decipher the sequen ce information available in data banks for the large group of glycoside hyd rolases (clan GH-A) to which these human lysosomal enzymes belong, we could deduce structure predictions for their catalytic domains and propose expla nations for the molecular effects of mutations described in patients. In ad dition, in the case of human P-glucuronidase for which experimental 3D data have been reported, we also show here that bioinformatics methods relying on the available 3D structure information can be used to obtain further Ins ights into the effects of various mutations described in patients with Sly disease. In a broader perspective, our work stresses that, in the context o f a rapid increase in protein sequence information through genome sequencin g, bioinformatics approaches might be highly useful for generating structur e-function predictions based on sequence-structure interrelationships.