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Biochim Biophys Acta. 2014 Feb;1844(2):316-22. doi: 10.1016/j.bbapap.2013.11.001. Epub 2013 Nov 10.

HMMpTM: improving transmembrane protein topology prediction using phosphorylation and glycosylation site prediction.

Author information

1
Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, Greece.
2
Department of Computer Science and Biomedical Informatics, University of Thessaly, Papasiopoulou 2-4, Lamia 35100, Greece.
3
Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, Greece. Electronic address: shamodr@biol.uoa.gr.

Abstract

During the last two decades a large number of computational methods have been developed for predicting transmembrane protein topology. Current predictors rely on topogenic signals in the protein sequence, such as the distribution of positively charged residues in extra-membrane loops and the existence of N-terminal signals. However, phosphorylation and glycosylation are post-translational modifications (PTMs) that occur in a compartment-specific manner and therefore the presence of a phosphorylation or glycosylation site in a transmembrane protein provides topological information. We examine the combination of phosphorylation and glycosylation site prediction with transmembrane protein topology prediction. We report the development of a Hidden Markov Model based method, capable of predicting the topology of transmembrane proteins and the existence of kinase specific phosphorylation and N/O-linked glycosylation sites along the protein sequence. Our method integrates a novel feature in transmembrane protein topology prediction, which results in improved performance for topology prediction and reliable prediction of phosphorylation and glycosylation sites. The method is freely available at http://bioinformatics.biol.uoa.gr/HMMpTM.

KEYWORDS:

Glycosylation; Hidden Markov model; Phosphorylation; Prediction; Topology; Transmembrane protein

PMID:
24225132
DOI:
10.1016/j.bbapap.2013.11.001
[Indexed for MEDLINE]

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