Literature DB >> 28879565

Comparative computational assessment of the pathogenicity of mutations in the Aspartoacylase enzyme.

C George Priya Doss1, Hatem Zayed2.   

Abstract

Aspartoacylase (ASPA) is a zinc-dependent abundant enzyme in the brain, which catalyzes the conversion of N-acetyl aspartate (NAA) into acetate and aspartate. Mutations in the ASPA gene are associated with the development of Canavan disease (CD), leading to the deficiency of ASPA activity. Patients with CD were characterized by degeneration of the white matter of the brain. We reported earlier on two patients with severe form of CD that both had two novel missense mutations in the ASPA: c.427 A > G; p. I143V and c.557 T > A; p. V186D (Zaki et al. 2017a), patient 1 harbored both mutations (p.I143V and p.V186D) in a heterozygous form together with four other mutations, and patient 2 had both mutations in homozygous form. Wijayasinghe et al. (2014) crystallized the 3D structures of four different ASPA mutants (p.K213E, p.Y231C, p.E285A, and p.F295S). In this study, we used in silico prediction methods and molecular dynamics simulation (MDS) to understand the structural impact of all these mutations. Moreover, we used molecular docking (MD) to investigate the binding patterns of the NAA substrate to the native and mutant proteins. Among the mutations, p.E285A (crystallized mutant) was predicted to be the most deleterious for the protein function and the least deleteriousness mutant was the p.I143V (novel mutant). Among the novel mutations, p.V186D was observed to be disruptive for both the zinc binding and NAA binding than the p.I143V. This study provides practical insights on the effect of these mutations on the ASPA function and might serve as a platform for drug design for CD treatment.

Entities:  

Keywords:  Aspartoacylase; Canavan disease; Genotype-phenotype correlation; Molecular dynamics simulation; Mutational assessment; Structure-function relationship; Zinc

Mesh:

Substances:

Year:  2017        PMID: 28879565     DOI: 10.1007/s11011-017-0090-5

Source DB:  PubMed          Journal:  Metab Brain Dis        ISSN: 0885-7490            Impact factor:   3.584


  48 in total

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  6 in total

1.  Molecular dynamics, residue network analysis, and cross-correlation matrix to characterize the deleterious missense mutations in GALE causing galactosemia III.

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2.  Computational modelling approaches as a potential platform to understand the molecular genetics association between Parkinson's and Gaucher diseases.

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3.  Impact of missense mutations in survival motor neuron protein (SMN1) leading to Spinal Muscular Atrophy (SMA): A computational approach.

Authors:  P Sneha; Tanzila U Zenith; Ummay Salma Abu Habib; Judith Evangeline; D Thirumal Kumar; C George Priya Doss; R Siva; Hatem Zayed
Journal:  Metab Brain Dis       Date:  2018-07-13       Impact factor: 3.584

4.  Computational approach to unravel the impact of missense mutations of proteins (D2HGDH and IDH2) causing D-2-hydroxyglutaric aciduria 2.

Authors:  D Thirumal Kumar; L Jerushah Emerald; C George Priya Doss; P Sneha; R Siva; W Charles Emmanuel Jebaraj; Hatem Zayed
Journal:  Metab Brain Dis       Date:  2018-07-09       Impact factor: 3.655

5.  LYRUS: a machine learning model for predicting the pathogenicity of missense variants.

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6.  Bioinformatics classification of mutations in patients with Mucopolysaccharidosis IIIA.

Authors:  Himani Tanwar; D Thirumal Kumar; C George Priya Doss; Hatem Zayed
Journal:  Metab Brain Dis       Date:  2019-08-05       Impact factor: 3.584

  6 in total

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