Evaluation of methods for predicting the topology of β-barrel outer membrane proteins and a consensus prediction method

We assess the statistical significance of the performance of each prediction scheme and conclude that Hidden Markov Model based methods, HMM-B2TMR, ProfTMB and PRED-TMBB, are currently the best predictors, according to either the per-residue accuracy, the segments overlap measure (SOV) or the total number of proteins with correctly predicted topologies in the test set. Furthermore, we show that the available predictors perform better when only transmembrane β-barrel domains are used for prediction, rather than the precursor full-length sequences, even though the HMM-based predictors are not influenced significantly. The consensus prediction method performs significantly better than each individual available predictor, since it increases the accuracy up to 4% regarding SOV and up to 15% in correctly predicted topologies.The consensus prediction method described in this work, optimizes the predicted topology with a dynamic programming algorithm and is implemented in a web-based application freely available to non-commercial users at http://bioinformatics.biol.uoa.gr/ConBBPRED webcite.Transmembrane proteins are divided to date into two structural classes, the α-helical membrane proteins and the β-barrel membrane proteins. Proteins of the α-helical membrane class have their membrane spanning regions formed by hydrophobic helices which consist of 15–35 residues [1]. These are the typical membrane proteins, found in cell membranes of eukaryotic cells and bacterial inner membranes [1]. On the other hand, β-barrel membrane proteins, have their transmembrane segments, formed by antiparallel β-strands, spanning the membrane in the form of a β-barrel [2,3]. These proteins are found solely in the outer membrane of the gram-negative bacteria, and presumably in the outer membranes of mitochondria and chloroplasts, a fact, perhaps, explained by the endosymbiotic theory [4-7]. Transmembrane protein topology prediction has been pursued for many years in bioinformatics, mostly focusi