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CW-PRED: A HMM-Based Method for the Classification of Cell Wall-Anchored Proteins of Gram-Positive Bacteria

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Artificial Intelligence: Theories and Applications (SETN 2012)

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Abstract

Gram-positive bacteria have surface proteins that are often implicated in virulence. A group of extracellular proteins attached to the cell wall contains an LPXTG-like motif that is target for cleavage and covalent coupling to peptidoglycan by sortase enzymes. A Hidden Markov Model (HMM) was developed for predicting the LPXTG and LPXTG-like cell-wall proteins of Gram-positive bacteria. The model is the first capable of predicting alternative (i.e. other than LPXTG-containing) substrates. Our analysis of 177 completely sequenced genomes identified 1456 cell-wall proteins, a number larger compared to the previously available methods. Among these, apart from the previously identified 1283 proteins carrying the LPXTG motif, we identified 39 newly identified proteins carrying NPXTG, 53 carrying LPXTA and 81 carrying the LAXTG motif. The tool is freely available for academic use at http://bioinformatics.biol.uoa.gr/CW-PRED/ .

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Fimereli, D.K., Tsirigos, K.D., Litou, Z.I., Liakopoulos, T.D., Bagos, P.G., Hamodrakas, S.J. (2012). CW-PRED: A HMM-Based Method for the Classification of Cell Wall-Anchored Proteins of Gram-Positive Bacteria. In: Maglogiannis, I., Plagianakos, V., Vlahavas, I. (eds) Artificial Intelligence: Theories and Applications. SETN 2012. Lecture Notes in Computer Science(), vol 7297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30448-4_36

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  • DOI: https://doi.org/10.1007/978-3-642-30448-4_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30447-7

  • Online ISBN: 978-3-642-30448-4

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