title: A combined transmembrane topology and signal peptide prediction method.
abstract: An inherent problem in transmembrane protein topology prediction and signal peptide prediction is the high similarity between the hydrophobic regions of a transmembrane helix and that of a signal peptide, leading to cross-reaction between the two types of predictions. To improve predictions further, it is therefore important to make a predictor that aims to discriminate between the two classes. In addition, topology information can be gained when successfully predicting a signal peptide leading a transmembrane protein since it dictates that the N terminus of the mature protein must be on the non-cytoplasmic side of the membrane. Here, we present Phobius, a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states. Training was done on a newly assembled and curated dataset. Compared to TMHMM and SignalP, errors coming from cross-prediction between transmembrane segments and signal peptides were reduced substantially by Phobius. False classifications of signal peptides were reduced from 26.1% to 3.9% and false classifications of transmembrane helices were reduced from 19.0% to 7.7%. Phobius was applied to the proteomes of Homo sapiens and Escherichia coli. Here we also noted a drastic reduction of false classifications compared to TMHMM/SignalP, suggesting that Phobius is well suited for whole-genome annotation of signal peptides and transmembrane regions. The method is available at as well as at
authors.affiliation: Center for Genomics and Bioinformatics, Karolinska Institutet, SE-17 177 Stockholm, Sweden.
authors.forename: Lukas
authors.initials: L
authors.lastname: Käll
authors.forename: Anders
authors.initials: A
authors.lastname: Krogh
authors.forename: Erik L L
authors.initials: EL
authors.lastname: Sonnhammer
mesh_terms: D008565:Membrane Proteins / Q000378:metabolism*; D008958:Models, Molecular; D021382:Protein Sorting Signals / Q000502:physiology*; D017433:Protein Structure, Secondary / Q000502:physiology*
chemical_list: D008565:Membrane Proteins; D021382:Protein Sorting Signals