Computational analysis of human N-acetylgalactosamine-6-sulfate sulfatase enzyme: an update in genotype–phenotype correlation for Morquio A

Research output: Contribution to JournalResearch Articlepeer-review

Abstract

Mucopolysaccharidosis IV A (MPS IV A) is a lysosomal storage disease produced by the deficiency of N-acetylgalactosamine-6-sulfate sulfatase (GALNS) enzyme. Although genotype–phenotype correlations have been reported, these approaches have not enabled to establish a complete genotype–phenotype correlation, and they have not considered a ligand–enzyme interaction. In this study, we expanded the in silico evaluation of GALNS mutations by using several bioinformatics tools. Tertiary GALNS structure was modeled and used for molecular docking against galactose-6-sulfate, N-acetylgalactosamine-6-sulfate, keratan sulfate, chondroitin-6-sulfate, and the artificial substrate 4-methylumbelliferyl-β-d-galactopyranoside-6-sulfate. Furthermore, we considered the evolutionary residue conservation, change conservativeness, position within GALNS structure, and the impact of amino acid substitution on the structure and function of GALNS. Molecular docking showed that amino acids involved in ligand interaction correlated with those observed in other human sulfatases, and mutations within the active cavity reduced affinity of all evaluated ligands. Combination of several bioinformatics approaches allowed to explaine 90 % of the missense mutations affecting GALNS, and the prediction of the phenotype for another 21 missense mutations. In summary, we have shown for the first time a docking evaluation of natural and artificial ligands for human GALNS, and proposed an update in genotype–phenotype correlation for Morquio A, based on the use of multiple parameters to predict the disease severity.

Original languageEnglish (US)
Pages (from-to)7073-7088
Number of pages16
JournalMolecular Biology Reports
Volume41
Issue number11
DOIs
StatePublished - Oct 21 2014
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics

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