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• W2101475413 abstract "In bacterial pathogens, both cell surface-exposed outer membrane proteins and proteins secreted into the extracellular environment play crucial roles in host-pathogen interaction and pathogenesis. Considerable efforts have been made to identify outer membrane (OM) and extracellular (EX) proteins produced by Leptospira interrogans, which may be used as novel targets for the development of infection markers and leptospirosis vaccines. In this study we used a novel computational framework based on combined prediction methods with deduction concept to identify putative OM and EX proteins encoded by the Leptospira interrogans genome. The framework consists of the following steps: (1) identifying proteins homologous to known proteins in subcellular localization databases derived from the consensus vote of computational predictions, (2) incorporating homology based search and structural information to enhance gene annotation and functional identification to infer the specific structural characters and localizations, and (3) developing a specific classifier for cytoplasmic proteins (CP) and cytoplasmic membrane proteins (CM) using Linear discriminant analysis (LDA). We have identified 114 putative EX and 63 putative OM proteins, of which 41% are conserved or hypothetical proteins containing sequence and/or protein folding structures similar to those of known EX and OM proteins. Overall results derived from the combined computational analysis correlate with the available experimental evidence. This is the most extensive in silico protein subcellular localization identification to date for Leptospira interrogans serovar Lai genome that may be useful in protein annotation, discovery of novel genes and understanding the biology of Leptospira." @default.
• W2101475413 created "2016-06-24" @default.
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• W2101475413 date "2008-01-01" @default.
• W2101475413 modified "2023-10-17" @default.
• W2101475413 title "Genome-wide subcellular localization of putative outer membrane and extracellular proteins in Leptospira interrogans serovar Lai genome using bioinformatics approaches" @default.
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• W2101475413 doi "https://doi.org/10.1186/1471-2164-9-181" @default.
• W2101475413 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2632647" @default.
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