TMBETADISC-RBF: Discrimination of beta-barrel membrane proteins using RBF networks and PSSM profiles.
Discriminating outer membrane proteins (OMPs) from other folding types of globular and membrane proteins is an important task both for identifying OMPs from genomic sequences and for the successful prediction of their secondary and tertiary structures. We have developed a method based on radial basis function networks and position specific scoring matrix (PSSM) profiles generated by PSI-BLAST and non-redundant protein database. Our approach with PSSM profiles has correctly predicted the OMPs with a cross-validated accuracy of 96.4% in a set of 1251 proteins, which contain 206 OMPs, 667 globular proteins and 378 alpha-helical inner membrane proteins. Furthermore, we applied our method on a dataset containing 114 OMPs, 187 TMH proteins and 195 globular proteins obtained with less than 20% sequence identity and obtained the cross-validated accuracy of 95%. This accuracy of discriminating OMPs is higher than other methods in the literature and our method could be used as an effective tool for dissecting OMPs from genomic sequences. We have developed a prediction server, TMBETADISC-RBF, which is available at http://rbf.bioinfo.tw/~sachen/OMP.html.
Ou
Yu-Yen
YY
Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan. yien@csie.org
Gromiha
M Michael
MM
Chen
Shu-An
SA
Suwa
Makiko
M
D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D030562:Databases, Protein; D004926:Escherichia coli / Q000235:genetics; D016680:Genome, Bacterial / Q000235:genetics; D008565:Membrane Proteins / Q000737:chemistry*; D016571:Neural Networks, Computer; D012984:Software
D000596:Amino Acids; D008565:Membrane Proteins