Transmembrane Prediction Server
This page has been developed for use locally (at the moment) for the prediction
of transmembrane helices in proteins. It is made available publically, but is
currently unsupported. If you have a major problem contact benjamin.hall (at)
bioch.ox.ac.uk (replace (at) with @) but the response is not guaranteed. This service was developed by John Cuthbertson and the following
reference should be cited if used in published work.
Transmembrane helix prediction: a comparative evaluation and analysis.
Protein Eng Des Sel. 2005 Jun;18(6):295-308
This work was funded by the MRC:
None of the original programs were
produced or developed by me:
Enter your query protein sequence into the form below. The sequence
should be in one letter code with no identifiers. A good site for converting between different sequence
formats is READSEQ
For a brief description of the method read the
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
Send your comments to email@example.com
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.
The HMMTOP transmembrane topology prediction server" Bioinformatics 17, 849-850
Comments to be sent to firstname.lastname@example.org.
- MEMSATv1.0 (the current version
available 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
Comments to be sent to email@example.com
White & Wimley (1999) Annu. Rev. Biophys. Biomolec. Struct. 28:319-365
Comments to Stephen White
(firstname.lastname@example.org) or to Sajith Jayasinghe
PHDhtm predicts the location and topology of transmembrane helices from multiple sequence alignments
Transmembrane 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, 1996
Comments to be sent to email@example.com
Please cite the following references when you publish the
results 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 to
firstname.lastname@example.org . Originally coded by Minoru Kanehisa
Membrane Protein Secondary Structure Prediction Server
The purpose of this server is to predict the transmembrane (TM) secondary
structures of membrane proteins, using the method of preference functions.
The method was invented by
Davor Juretic, professor at the
University of Split, Croatia. This server was written by
Damir Zucic,at the
University of Osijek
Ana Jeroncic was involved both in development of the prediction program and
in testing of this server. Click
to read more about Prof. Davor Juretic group.
For comments contact
prof. dr. Davor Juretic
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 above
references in publications (or other types of presentation).
Send your comments to Bengt.Persson@mbb.ki.se
Liu, L.-P. and Deber, C.M.: Guidelines for Membrane Protein Engineerin
g Derived from de novo Designed Model Peptides. Biopolymers (Peptide
Science) 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)
Liu, L.-P. and Deber, C.M.: Combining Hydrophobicity and Helicity: A Novel Approach to Membrane Protein Structure Prediction. Bioorg & Med. Chem.7, 1-7 (1999). (Abstract)
Feel free to send comments to email@example.com.
TMHMM is described in:
Anders Krogh and Bjorn Larsson, Gunnar von Heijne, and Erik L.L. Sonnhammer:
Predicting Transmembrane Protein Topology with a Hidden Markov
Model: Application to Complete Genomes.
J. Mol. Biol. 305:567-580, 2001.
Erik L.L. Sonnhammer, Gunnar von Heijne, and Anders Krogh:
A hidden Markov model for predicting transmembrane helices in protein
In J. Glasgow et al., eds.: Proc. Sixth Int. Conf. on Intelligent
Systems for Molecular Biology, pages 175-182. AAAI Press, 1998.
Comments to be sent to Anders Krogh, firstname.lastname@example.org
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 segments
Biol. Chem. Hoppe-Seyler 347,166
For further information see the TMbase
Comments to be sent to email@example.com
Topology prediction of membrane proteins
von 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.
Comments to be sent to firstname.lastname@example.org