TMBETADISC-RBF: discrimination of \(\beta\)-barrel membrane proteins using RBF networks and PSSM profiles. (English) Zbl 1403.92218

Summary: 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.


92D20 Protein sequences, DNA sequences
Full Text: DOI


[1] Altschul, S.; Madden, T.; Schaffer, A.; Zhang, J.; Zhang, Z.; Miller, W.; Lipman, D., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic acids res., 25, 17, 3389-3402, (1997)
[2] Bagos, P.; Liakopoulos, T.; Spyropoulos, I.; Hamodrakas, S., A hidden Markov model method, capable of predicting and discriminating beta-barrel outer membrane proteins, BMC bioinformatics, 5, 1, 29, (2004)
[3] Berven, F.; Flikka, K.; Jensen, H.; Eidhammer, I., BOMP: a program to predict integral b-barrel outer membrane proteins encoded within genomes of Gram-negative bacteria, Nucleic acids res., 32, W394-W399, (2004)
[4] Bigelow, H.; Rost, B., Proftmb: a web server for predicting bacterial transmembrane beta barrel proteins, Nucleic acids res., 34, web server issue, W186, (2006)
[5] Chandonia, J.; Hon, G.; Walker, N.; Conte, L.; Koehl, P.; Levitt, M.; Brenner, S.; Journals, O., The ASTRAL compendium in 2004, Nucleic acids res., 32, D189-D192, (2004)
[6] Garrow, A.; Agnew, A.; Westhead, D., TMB-hunt: a web server to screen sequence sets for transmembrane beta-barrel proteins, Nucleic acids res., 33, W188-W192, (2005)
[7] Garrow, A.G.; Westhead, D.R., A consensus algorithm to screen genomes for novel families of transmembrane beta barrel proteins, Proteins, 69, 1, 8-18, (2007)
[8] Gnanasekaran, T.; Peri, S.; Arockiasamy, A.; Krishnaswamy, S., Profiles from structure based sequence alignment of porins can identify \(\beta\) stranded integral membrane proteins, Bioinformatics, 16, 839-842, (2000)
[9] Gromiha, M.M., Motifs in outer membrane protein sequences, Biophys. chem., 117, 65-71, (2005)
[10] Gromiha, M.M.; Ahmad, S.; Suwa, M., Application of residue distribution along the sequence for discriminating outer membrane proteins, Comput. biol. chem., 29, 135-142, (2005) · Zbl 1096.92015
[11] Gromiha, M.M.; Suwa, M., A simple statistical method for discriminating outer membrane proteins with better accuracy, Bioinformatics, 21, 961-968, (2005)
[12] Gromiha, M.M.; Suwa, M., Discrimination of outer membrane proteins using machine learning algorithms, Proteins: structure, function, and bioinformatics, 63, 1031-1037, (2006)
[13] Gromiha, M.M.; Suwa, M., Current developments on-barrel membrane proteins: sequence and structure analysis, discrimination and prediction, Curr. protein pept. sci., 8, 6, 580-599, (2007)
[14] Jones, D.T., Protein secondary structure prediction based on position-specific scoring matrices, J. mol. biol., 292, 195-202, (1999)
[15] Li, W.; Jaroszewski, L.; Godzik, A., Clustering of highly homologous sequences to reduce the size of large protein databases, Bioinformatics, 17, 282-283, (2001)
[16] Liu, Q.; Zhu, Y.; Wang, B.; Li, Y., Identification of b-barrel membrane proteins based on amino acid composition properties and predicted secondary structure, Comput. biol. chem., 27, 355-361, (2003)
[17] Martelli, P.L.; Fariselli, P.; Krogh, A.; Casadio, R., A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteins, Bioinformatics, 18, 46-53, (2002)
[18] Murzin, A.G.; Brenner, S.E.; Hubbard, T.; Chothia, C., SCOP: a structural classification of proteins database for the investigation of sequences and structures, J. mol. biol., 247, 536-540, (1995)
[19] Natt, N.K.; Kaur, H.; Raghava, G.P.S., Prediction of transmembrane regions of beta-barrel proteins using ann and svm-based methods, Proteins, 56, 11-18, (2004)
[20] Ou, Y.-Y.; Oyang, Y.-J.; Chen, C.-Y., A novel radial basis function network classifier with centers set by hierarchical clustering, (), 1383-1388
[21] Park, K.-J.; Gromiha, M.M.; Horton, P.; Suwa, M., Discrimination of outer membrane proteins using support vector machines, Bioinformatics, 21, 4223-4229, (2005)
[22] Press, W.H., Numerical recipes in C, (1992), Cambridge University Press Cambridge
[23] Saier, M.; Tran, C.; Barabote, R., TCDB: the transporter classification database for membrane transport protein analyses and information, Nucleic acids res., 34, D181-D186, (2006)
[24] Su, C.-T.; Chen, C.-Y.; Ou, Y.-Y., Protein disorder prediction by condensed PSSM considering propensity for order or disorder, BMC bioinformatics, 7, 1, 319, (2006)
[25] Takasaki, S.; Kawamura, Y.; Konagaya, A., Selecting effective sirna sequences by using radial basis function network and decision tree learning, BMC bioinformatics, 7, 5, S22, (2006)
[26] Tusnády, G.; Dosztányi, Z.; Simon, I., PDB_TM: selection and membrane localization of transmembrane proteins in the protein data bank, Nucleic acids res., 33, D275-D278, (2005)
[27] Witten, I.; Frank, E., Data mining:: practical machine learning tools and techniques, (2005), Morgan Kaufmann · Zbl 1076.68555
[28] Xie, D.; Li, A.; Wang, M.; Fan, Z.; Feng, H., LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST, Nucleic acids res., 33, 1, W105-W110, (2005)
[29] Yang, Z.; Thomson, R., Bio-basis function neural network for prediction of protease cleavage sites in proteins, Neural netw. IEEE trans., 16, 1, 263-274, (2005)
[30] Zhang, G.; Huang, D., Prediction of inter-residue contacts map based on genetic algorithm optimized radial basis function neural network and binary input encoding scheme, J. comput. aided mol. des., 18, 12, 797-810, (2004)
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