Prediction of lipoprotein signal peptides in Gram-negative bacteria.
Protein Sci
; 12(8): 1652-62, 2003 Aug.
Article
em En
| MEDLINE
| ID: mdl-12876315
ABSTRACT
A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Proteínas de Bactérias
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Sinais Direcionadores de Proteínas
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Biologia Computacional
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Bactérias Gram-Negativas
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Lipoproteínas
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Ano de publicação:
2003
Tipo de documento:
Article