Transmembrane Prediction Server (2024)

DAS

For a brief description of the method read the abstract.

Please cite: M. Cserzo, E. Wallin, I. Simon, G. von Heijne and A. Elofsson: Prediction of transmembrane alpha-helices in procariotic membrane proteins: the Dense Alignment Surface method; Prot. Eng. vol. 10, no. 6, 673-676, 1997

HMMTOP

The method is described in "G.E Tusnády and I. Simon(1998) Principles Governing Amino Acid Composition of Integral Membrane Proteins:Applications to Topology Prediction." J. Mol. Biol. 283, 489-506. New features of HMMTOP 2.0 are described in "G.E Tusnády and I.Simon(2001). The HMMTOP transmembrane topology prediction server" Bioinformatics 17, 849-850

MEMSATv1.0 (the current versionavailable online is version 2)

Jones, D. T., Taylor, W. R., Thornton, J. M. (1994) A Model Recognition Approach to the Prediction of All-Helical Membrane Protein Structure and Topology. Biochem. 33: 3038-3049

MPEx

White & Wimley (1999) Annu. Rev. Biophys. Biomolec. Struct. 28:319-365

PHD

PHDhtm predicts the location and topology of transmembrane helices from multiple sequence alignmentsTransmembrane helices in integral membrane proteins are predicted by a system of neural networks. The shortcoming of the network system is that often too long helices are predicted. These are cut by an empirical filter. The final prediction (Rost et al., Protein Science, 1995, 4, 521-533) has an expected per-residue accuracy of about 95%. The number of false positives, i.e., transmembrane helices predicted in globular proteins, is about 2% (Rost et al. 1996). The neural network prediction of transmembrane helices (PHDhtm) is refined by a dynamic programming-like algorithm. This method resulted in correct predictions of all transmembrane helices for 89% of the 131 proteins used in a cross-validation test; more than 98% of the transmembrane helices were correctly predicted. The output of this method is used to predict topology, i.e., the orientation of the N-term with respect to the membrane. The expected accuracy of the topology prediction is > 86%. Prediction accuracy is higher than average for eukaryotic proteins and lower than average for prokaryotes. PHDtopology was more accurate than all other methods tested on identical data sets in 1996 (Rost, Casadio & Fariselli, 1996a and 1996b). B Rost: PHD: predicting one-dimensional protein structure by profile based neural networks. Methods in Enzymology, 266, 525-539, 1996.B Rost, P Fariselli, and R Casadio: Topology prediction for helical transmembrane proteins at 86% accuracy. Protein Science, 7, 1704-1718, 1996Comments to be sent to rost@columbia.edu

ALOM2

Please cite the following references when you publish theresults of this program. Klein, P., Kanehisa, M., and De Lisi, C., Biochim. Biophys.Acta, 815, 468-476, 1985.(for the modification using two threshold parameters:)Nakai, K., and Kanehisa, M., Genomics 14, 897-911, 1992.Any comments tonakai@imcb.osaka-u.ac.jp . Originally coded by Minoru Kanehisa

SPLIT4.0

Membrane Protein Secondary Structure Prediction Server

TMAP

This program predicts transmembrane segments in proteins, utilising the algorithm described in: "Persson, B. & Argos, P. (1994) Prediction of transmembrane segments in proteins utilsing multiple sequence alignments J. Mol. Biol. 237, 182-192."and "Persson, B. & Argos, P. (1996) Topology prediction of membrane proteins Prot. Sci. 5, 363-371" Users of this program are kindly asked to cite the abovereferences in publications (or other types of presentation).Send your comments to Bengt.Persson@mbb.ki.se

TM-Finder

Liu, L.-P. and Deber, C.M.: Guidelines for Membrane Protein Engineering Derived from de novo Designed Model Peptides. Biopolymers (PeptideScience) 47, 41-62 (1998). (Abstract)

Liu, L.-P. and Deber, C.M.: Uncoupling Protein Hydrophobicity and Helicity in Nonpolar Environments. J. Biol. Chem 273, 23645-23648 (1998). (Abstract)

TMHMM2.0

TMHMM is described in:

TMpred

The TMpred program makes a prediction of membrane-spanning regions and their orientation. The algorithm is based on the statistical analysis of TMbase, a database of naturally occuring transmembrane proteins. The prediction is made using a combination of several weight-matrices for scoring.K. Hofmann & W. Stoffel (1993) TMbase - A database of membrane spanning proteins segmentsBiol. Chem. Hoppe-Seyler 347,166

For further information see the TMbase

TopPred2

Topology prediction of membrane proteinsvon Heijne, G. (1992) Membrane Protein Structure Prediction: Hydrophobicity Analysis and the 'Positive Inside' Rule. J.Mol.Biol. 225, 487-494. Claros, M.G., and von Heijne, G. (1994) TopPred II: An Improved Software For Membrane Protein Structure Predictions. CABIOS 10, 685-686. Deveaud and Schuerer (Pasteur Institute) new implementation of the original toppred program, based on G. von Heijne algorithm.