title: OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method.
abstract: In the two transmembrane protein types, outer membrane proteins (OMPs) perform diverse important biochemical functions, including substrate transport and passive nutrient uptake and intake. Hence their 3D structures are expected to reveal these functions. Because experimental structures are scarce, predicted 3D structures are more adapted to OMP research instead, and the inter-barrel residue contact is becoming one of the most remarkable features, improving prediction accuracy by describing the structural information of OMPs. To predict OMP structures accurately, we explored an OMP inter-barrel residue contact prediction method: OMPcontact. Multiple OMP-specific features were integrated in the method, including residue evolutionary covariation, topology-based transmembrane segment relative residue position, OMP lipid layer accessibility, and residue evolution conservation. These features describe the properties of a residue pair in different respects: sequential, structural, evolutionary, and biochemical. Within a 3-residues slide window, a Support Vector Machine (SVM) could accurately determinate the inter-barrel contact residue pair using above features. A 5-fold cross-valuation process was applied in testing the OMPcontact performance against a non-redundant OMP set with 75 samples inside. The tests compared four evolutionary covariation methods and screen analyzed the adaptive ones for inter-barrel contact prediction. The results showed our method not only efficiently realized the prediction, but also scored the possibility for residue pairs reliably. This is expected to improve OMP tertiary structure prediction. Therefore, OMPcontact will be helpful in compiling a structural census of outer membrane protein.
authors: 1 School of Computer Science and Technology, Jilin University , Changchun, China .|4 School of Computer Science and Engineering, Changchun University of Technology , Changchun, China .
authors: Li
authors: L
authors: Zhang
authors: 2 School of Computer Science and Information Technology, Northeast Normal University , Changchun, China .
authors: Han
authors: H
authors: Wang
authors: 1 School of Computer Science and Technology, Jilin University , Changchun, China .
authors: Lun
authors: L
authors: Yan
authors: 1 School of Computer Science and Technology, Jilin University , Changchun, China .
authors: Lingtao
authors: L
authors: Su
authors: 3 Department of Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri , Columbia, Missouri, U.S.A.
authors: Dong
authors: D
authors: Xu
mesh_terms: D001425:Bacterial Outer Membrane Proteins / Q000737:chemistry*; D001692:Biological Transport; D030562:Databases, Protein; D008563:Membrane Lipids / Q000737:chemistry*; D000072756:Protein Conformation, alpha-Helical; D000072757:Protein Conformation, beta-Strand; D054730:Protein Interaction Domains and Motifs; D017434:Protein Structure, Tertiary; D060388:Support Vector Machine
chemical_list: D001425:Bacterial Outer Membrane Proteins; D008563:Membrane Lipids
keywords: contact prediction; evolutionary covariation; outer membrane protein; structure prediction