Biblioteca Digital do Instituto Politécnico de Bragança   Instituto Politécnico de Bragança

Biblioteca Digital do IPB >
Escola Superior de Saúde >
Departamento de Ciências da Vida e Saúde Pública >
CVSP - Resumos em Proceedings Não Indexados ao ISI >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/6362

Título: Prediction of deleterious nsSNPs in human UGT1A1 gene by web available algorithm tools
Autor: Rodrigues, Carina
Costa, Elísio
Vieira, Emília
Santos, Rosário
Santos-Silva, Alice
Bronze-da-Rocha, Elsa
Palavras-chave: NsSNPs
Human UGT1A1 gene
Issue Date: 2011
Editora: Mutation Detection 2011
Citação: Rodrigues, Carina; Costa, Elísio; Vieira, Emília; Santos, Rosário; Santos-Silva, Alice; Bronze-da-Rocha, Elsa (2011) - Prediction of deleterious nsSNPs in human UGT1A1 gene by web available algorithm tools. In XI International Symposium on Mutations in the Genome. Santorini, Grécia.
Resumo: The uridine diphosphate glucuronosyltransferase (UGT1A1) belongs to the class of phase II enzymes involved in the metabolism and detoxification of numerous xenobiotic and endogenous compounds (e.g. bilirubin). Genotyping data lead to the discovery of over 100 single nucleotide polymorphisms (SNPs) within the UGT1A1 gene. Some of the non-synonymous (ns) SNPs (nsSNPs) of the human UGT1A1 gene variants have been associated to hyperbilirubinemia in Gilbert’s and Crigler-Najjar syndromes, as well as altered drug clearance and/or drug response. In UGT1A1, and other genes, there are many nsSNPs which genotype-phenotype correlations were not established, since the study of the functional impact of all SNPs is time consuming and expensive. Alternatively, bioinformatics tools have gained an increased importance with the prospect of reducing the totality of detailed studies at protein level. The aim of this study was to investigate the potential of bioinformatics approaches, using five web available algorithms [Sorting Intolerant from Tolerant (SIFT); polymorphism phenotyping-2 (PolyPhen-2); Align Grantham Variance/Grantham Difference (Align-GVGD); Multivariate Analysis of Protein Polymorphism (MAPP); Block Substitution Matrix score 62 (BLOSUM62)], to predict the phenotype of 28 human UGT1A1 nsSNPs, previously characterized at protein level by in vivo and in vitro studies. From those, 24 SNPs were confirmed as responsible for changes in protein function and in 4 there were no detected impact. Information describing the UGT1A1 variants was obtained from mutation database websites: http://www.polydoms.cchmc.org/polydoms, http://www.mutdb.org, and http://www.ncbi.nlm.nih.gov/sites/entrez. Results from in silico analysis showed a correct prediction rate of 85.7% for Polyphen-2, 82.0% for both BLOSUM62 and SIFT, 60.7% for MAPP and 32.1% for Align-GVGD. In the total of 28 studied variants, 78.6% (n=22) had concordant results using Polyphen-2 and SIFT algorithms and 57.1% (n=16) using Polyphen-2, SIFT and BLOSUM62. Concordance in variants prediction, between the five used methods and with results obtained at protein levels, was observed in 14.3% (n=4) nsSNPs. In conclusion, our results showed that SIFT and Polyphen together, were the best predictor methods of nsSNPs phenotype in human UGT1A1 gene. These tools have the advantage of directing and complement functional assays. However, the observed discrepancy in variants prediction phenotype may be improved with a method combining all currently available criterions.
Arbitragem científica: yes
URI: http://hdl.handle.net/10198/6362
Versão do Editor: www.mutationdetection.org/santorini/Em cache - Similares
Appears in Collections:CVSP - Resumos em Proceedings Não Indexados ao ISI

Files in This Item:

File Description SizeFormat
Santorini 2011[1].pdf866,03 kBAdobe PDFView/Open

Statistics
FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpaceOrkut
Formato BibTex mendeley Endnote Logotipo do DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 


  © Instituto Politécnico de Bragança - Biblioteca Digital - Feedback - Statistics
  Estamos no RCAAP Governo Português separator Ministério da Educação e Ciência   Fundação para a Ciência e a Tecnologia

Financiado por:

POS_C UE