Systematic exploration of predicted destabilizing nonsynonymous single nucleotide polymorphisms (nsSNPs) of human aldehyde oxidase: A Bio-informatics study

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Abstract

Aldehyde Oxidase (hAOX1) is a cytosolic enzyme involved in the metabolism of drugs and xenobiotic compounds. The enzyme belongs to the xanthine oxidase (XO) family of Mo containing enzyme and is a homo-dimer of two 150 kDa monomers. Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs) of hAOX1 have been reported as affecting the ability of the enzyme to metabolize different substrates. Some of these nsSNPs have been biochemically and structurally characterized but the lack of a systematic and comprehensive study regarding all described and validated nsSNPs is urgent, due to the increasing importance of the enzyme in drug development, personalized medicine and therapy, as well as in pharmacogenetic studies. The objective of the present work was to collect all described nsSNPs of hAOX1 and utilize a series of bioinformatics tools to predict their effect on protein structure stability with putative implications on phenotypic functional consequences. Of 526 nsSNPs reported in NCBI-dbSNP, 119 are identified as deleterious whereas 92 are identified as nondeleterious variants. The stability analysis was performed for 119 deleterious variants and the results suggest that 104 nsSNPs may be responsible for destabilizing the protein structure, whereas five variants may increase the protein stability. Four nsSNPs do not have any impact on protein structure (neutral nsSNPs) of hAOX1. The prediction results of the remaining six nsSNPs are nonconclusive. The in silico results were compared with available experimental data. This methodology can also be used to identify and prioritize the stabilizing and destabilizing variants in other enzymes involved in drug metabolism.

Original languageEnglish
Article numbere00538
JournalPharmacology Research and Perspectives
Volume7
Issue number6
DOIs
Publication statusPublished - 1 Dec 2019

Keywords

  • aldehyde oxidase
  • computational genomic
  • in silico analysis
  • pharmacogenetic
  • single nucleotide polymorphism

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