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Advisor(s)
Abstract(s)
Variations in the gene encoding uridine
diphosphate glucuronosyltransferase 1A1 (UGT1A1) are
particularly important because they have been associated
with hyperbilirubinemia in Gilbert’s and Crigler–Najjar
syndromes as well as with changes in drug metabolism.
Several variants associated with these phenotypes are nonsynonymous
single-nucleotide polymorphisms (nsSNPs).
Bioinformatics approaches have gained increasing importance
in predicting the functional significance of these
variants. This study was focused on the predictive ability
of bioinformatics approaches to determine the pathogenicity
of human UGT1A1 nsSNPs, which were previously
characterized at the protein level by in vivo and in
vitro studies. Using 16 Web algorithms, we evaluated 48
nsSNPs described in the literature and databases. Eight
of these algorithms reached or exceeded 90% sensitivity
and six presented a Matthews correlation coefficient above
0.46. The best-performing method was MutPred, followed
by Sorting Intolerant from Tolerant (SIFT). The prediction
measures varied significantly when predictors such
us SIFT, polyphen-2, and Prediction of Pathological Mutations
on Proteins were run with their native alignment
generated by the tool, or with an input alignment that was
strictly built with UGT1A1 orthologs and manually curated.
Our results showed that the prediction performance
of some methods based on sequence conservation analysis
can be negatively affected when nsSNPs are positioned
at the hypervariable or constant regions of UGT1A1
ortholog sequences.
Description
Keywords
nsSNPs Genotype Bioinformatics Phenotype Protein function
Citation
Rodrigues, Carina; Santos-Silva, Alice; Costa, Elísio; Bronze-da-Rocha, Elsa (2015). Performance of in silico tools for the evaluation of UGT1A1 missense variants. Human Mutation. ISSN 1098-1004. 36:12,1215–1225
Publisher
Wiley-Blackwell