What are the computational methods for the prediction of beta-barrel transmembrane proteins?
Computational tools have been developed for beta-barrel transmembrane protein discrimination, topology prediction and prediction of their structural features.
Initial methods developed for the prediction of the transmembrane beta strands were based on hydrophobicity analysis, using sliding windows along the sequence, in order to capture the alternating patterns of hydrophobic-hydrophilic residues of the transmembrane strands, or using generalized secondary structure prediction methods. Other approaches included the construction of special empirical rules using amino-acid propensities and prior knowledge of the structural nature of the proteins, and the development of Neural Network-based predictors to predict the location of alpha-carbon atoms with respect to the membrane. During the last few years, other more refined methods, appeared, including: Neural Networks, Hidden Markov Models, Support Vector Machines, k-Nearest Neighbors, Radial Basis Functions, Bayesian Networks, Genetic Algorithms, Mahalanobis Discriminant Functions, Cellular Automata, N-to-1 Extreme Learning Machines. Hidden Markov Model-based methods are among the most successful in topology prediction, being able to capture the unique architecture of beta-barrel transmembrane proteins. Consensus methods, as well as pipelines of several related tools (e.g. subcellular localization prediciton, alpha-helical transmembrane protein prediction, signal-peptide/lipoprotein prediction) have also used for discriminating beta-barrel transmembrane proteins. Recently, a number of methods for predicting more detailed structural features (e.g. surface accessibility, residue contacts, even detailed atomic 3D models) tailored to beta-barrel transmembrane proteins have been developed, based on knowledge-based potential functions, graph theoretic models, physical models and multi-tape S-attribute grammars. Methods/tools falling in the aforementioned classes are (listed in alphabetical order): BBF (beta-barrel finder), BETAWARE, BOCTOPUS, BOMP, BTMX (Beta barrel TransMembrane eXposure), HHomp, HMM-B2TMR, OMBBpred, PROFtmb, PRED-TMBB, TMB-Hunt, TBBPred, TMBETAPRED-RBF, TMBHMM, TransFold, TMBpro, TMBKNN, Wimley