Research Article

The AAPS Journal

, Volume 11, Issue 3, pp 469-480

First online:

Prediction of Deleterious Non-synonymous Single-Nucleotide Polymorphisms of Human Uridine Diphosphate Glucuronosyltransferase Genes

  • Yuan Ming DiAffiliated withDiscipline of Chinese Medicine, School of Health Sciences, RMIT University
  • , Eli ChanAffiliated withDepartment of Pharmacy, Faculty of Science, National University of Singapore
  • , Ming Qian WeiAffiliated withDivision of Molecular and Gene Therapies, School of Medical Science, Griffith University
  • , Jun-Ping LiuAffiliated withDepartment of Immunology, Central and Eastern Clinical School, Monash University
  • , Shu-Feng ZhouAffiliated withDiscipline of Chinese Medicine, School of Health Sciences, RMIT University Email author 


UDP glucuronosyltransferases (UGTs) are an important class of Phase II enzymes involved in the metabolism and detoxification of numerous xenobiotics including therapeutic drugs and endogenous compounds (e.g. bilirubin). To date, there are 21 human UGT genes identified, and most of them contain single-nucleotide polymorphisms (SNPs). Non-synonymous SNPs (nsSNPs) of the human UGT genes may cause absent or reduced enzyme activity and polymorphisms of UGT have been found to be closely related to altered drug clearance and/or drug response, hyperbilirubinemia, Gilbert’s syndrome, and Crigler-Najjar syndrome. However, it is unlikely to study the functional impact of all identified nsSNPs in humans using laboratory approach due to its giant number. We have investigated the potential for bioinformatics approach for the prediction of phenotype based on known nsSNPs. We have identified a total of 248 nsSNPs from human UGT genes. The two algorithms tools, sorting intolerant from tolerant (SIFT) and polymorphism phenotyping (PolyPhen), were used to predict the impact of these nsSNPs on protein function. SIFT classified 35.5% of the UGT nsSNPs as “deleterious”; while PolyPhen identified 46.0% of the UGT nsSNPs as “potentially damaging” and “damaging”. The results from the two algorithms were highly associated. Among 63 functionally characterized nsSNPs in the UGTs, 24 showed altered enzyme expression/activities and 45 were associated with disease susceptibility. SIFT and Polyphen had a correct prediction rate of 57.1% and 66.7%, respectively. These findings demonstrate the potential use of bioinformatics techniques to predict genotype–phenotype relationships which may constitute the basis for future functional studies.

Key words

phenotype PolyPhen SIFT SNP UGT