Discrimination of outer membrane proteins with improved performance

This paper presents a method for distinguishing outer membrane proteins (OMPs) from non-OMPs (that is, globular proteins and inner membrane proteins (IMPs)). First, we calculated the average residue compositions of OMPs, globular proteins and IMPs separately using a training set. Then for each protein from the test set, its distances to the three groups were calculated based on residue composition using a weighted Euclidean distance (WED) approach. Proteins from the test set were classified into OMP versus non-OMP classes based on the least distance. The proposed method can distinguish between OMPs and non-OMPs with 91.0% accuracy and 0.639 Matthews correlation coefficient (MCC). We then improved the method by including homologous sequences into the calculation of residue composition and using a feature-selection method to select the single residue and di-peptides that were useful for OMP prediction. The final method achieves an accuracy of 96.8% with 0.859 MCC. In direct comparisons, the proposed method outperforms previously published methods.The proposed method can identify OMPs with improved performance. It will be very helpful to the discovery of OMPs in a genome scale.Outer membrane proteins (OMPs) perform diverse functional roles, including bacterial adhesion, structural integrity of the cell wall, and material transport [1-3]. The membrane-spanning regions of OMPs form a characteristic β-barrel. Discriminating OMPs from other proteins and identifying membrane spanning β-barrels in them are crucial for many studies. Unlike α-helical membrane proteins, which can be easily identified based on long stretches of hydrophobic residues, OMPs are more difficult to predict, mainly due to shorter membrane-spanning regions with higher variations in properties [3]. Nevertheless, several methods have been proposed for this task. Gnanasekaran et al. [4] used profiles developed from structure-based alignments of porins to identify OMPs. Wimley et al. [5] analyzed the struct