Structural interpretation of mutations in phenylalanine hydroxylase protein aids in identifying genotype–phenotype correlations in phenylketonuria

IG Jennings, RGH Cotton, B Kobe - European Journal of Human …, 2000 - nature.com
IG Jennings, RGH Cotton, B Kobe
European Journal of Human Genetics, 2000nature.com
Phenylalanine hydroxylase (PAH) is the enzyme that converts phenylalanine to tyrosine as a
rate-limiting step in phenylalanine catabolism and protein and neurotransmitter
biosynthesis. Over 300 mutations have been identified in the gene encoding PAH that result
in a deficient enzyme activity and lead to the disorders hyperphenylalaninaemia and
phenylketonuria. The determination of the crystal structure of PAH now allows the
determination of the structural basis of mutations resulting in PAH deficiency. We present an …
Abstract
Phenylalanine hydroxylase (PAH) is the enzyme that converts phenylalanine to tyrosine as a rate-limiting step in phenylalanine catabolism and protein and neurotransmitter biosynthesis. Over 300 mutations have been identified in the gene encoding PAH that result in a deficient enzyme activity and lead to the disorders hyperphenylalaninaemia and phenylketonuria. The determination of the crystal structure of PAH now allows the determination of the structural basis of mutations resulting in PAH deficiency. We present an analysis of the structural basis of 120 mutations with a ‘classified’biochemical phenotype and/or available in vitro expression data. We find that the mutations can be grouped into five structural categories, based on the distinct expected structural and functional effects of the mutations in each category. Missense mutations and small amino acid deletions are found in three categories:‘active site mutations’,‘dimer interface mutations’, and ‘domain structure mutations’. Nonsense mutations and splicing mutations form the category of ‘proteins with truncations and large deletions’. The final category,‘fusion proteins’, is caused by frameshift mutations. We show that the structural information helps formulate some rules that will help predict the likely effects of unclassified and newly discovered mutations: proteins with truncations and large deletions, fusion proteins and active site mutations generally cause severe phenotypes; domain structure mutations and dimer interface mutations spread over a range of phenotypes, but domain structure mutations in the catalytic domain are more likely to be severe than domain structure mutations in the regulatory domain or dimer interface mutations.
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