TOPCONS Thursday, October 23 2014
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1. Summary

Given the amino acid sequence of a putative alpha-helical membrane protein, TOPCONS predicts the topology of the protein, i.e. a specification of the membrane spanning segments and their IN/OUT orientation relative to the membrane. The prediction is a consensus from five different topology prediction algorithms: SCAMPI (single sequence mode), SCAMPI (multiple sequence mode), PRODIV-TMHMM, PRO-TMHMM and OCTOPUS. These five predictions are used as input to the TOPCONS hidden Markov model (HMM), which gives a consensus prediction for the protein, together with a reliability score based on the agreement of the included methods across the sequence. In addition, ZPRED is used to predict the Z-coordinate (i.e. the distance to the membrane center) of each amino acid, and the ΔG-scale is used to predict the free energy of membrane insertion for a window of 21 amino acids centered around each position in the sequence. For an explanation of the methods included in the server, see the corresponding links in the left hand menu.

Note that the server does not predict cleavable signal peptides, which are easily confused with TM segments. If signal peptides are likely to be present in the input data, a separate signal peptide predictor such as SignalP should first be applied and predicted signal peptides cleaved off before submitting the sequence to TOPCONS.


 
2. Usage

Input to the server is an amino acid sequence in FASTA format. Due to computational limitations, only one sequence per query is allowed. For large benchmark sets and full proteome scans, use the SCAMPI server instead. A sequence profile is created for the input sequence using BLAST, and this profile is used as input to all the different methods (except SCAMPI-seq, where only the query sequence is used).

Example input:
>sp|O93740|BACR_HALS4 Bacteriorhodopsin Halobacterium sp.
MCCAALAPPMAATVGPESIWLWIGTIGMTLGTLYFVGRGRGVRDRKMQEFYIITIFITTI
AAAMYFAMATGFGVTEVMVGDEALTIYWARYADWLFTTPLLLLDLSLLAGANRNTIATLI
GLDVFMIGTGAIAALSSTPGTRIAWWAISTGALLALLYVLVGTLSENARNRAPEVASLFG
RLRNLVIALWFLYPVVWILGTEGTFGILPLYWETAAFMVLDLSAKVGFGVILLQSRSVLE
RVATPTAAPT

Optionally, parts of the sequence can be constrained to a known Inside/Outside/Membrane-location, by clicking the Restrainment options. Apart from N- and C-terminal constraints, any type of constraint can be entered in the Other textbox using the format: [first]-[last]-[label]; where [first] is first residue and [last] is last residue in restrained range, and [label] is i (Inside), o (Outside) or M (Membrane).

Example:
1-1-o;20-25-M;


 
3. Output

The server outputs the topology predictions using all the individual methods, as well as the consensus prediction (TOPCONS). In addition, predicted Z-coordinates, predicted ΔG-values and reliability scores are given for each position in the sequence. The results are both displayed graphically and are available for download in text format in the TOPCONS result file. The BLAST output, which is used as input to the methods, is available in the BLAST result file. High-resolution versions of the images are also available for download.


 
4. References

TOPCONS:
TOPCONS: consensus prediction of membrane protein topology. Andreas Bernsel, Håkan Viklund, Aron Hennerdal and Arne Elofsson (2009) Nucleic Acids Research 37(Webserver issue), W465-8 [PubMed]
SCAMPI:
Prediction of membrane-protein topology from first principles. Andreas Bernsel, Håkan Viklund, Jenny Falk, Erik Lindahl, Gunnar von Heijne and Arne Elofsson (2008) Proc. Natl. Acad. Sci. USA. 105, 7177-7181. [Pubmed]
OCTOPUS:
A method that improves topology prediction for transmembrane proteins by using two-track ANN-based preference scores and an improved topological grammar. Håkan Viklund and Arne Elofsson (2008) Bioinformatics. 24, 1662-1668. [Pubmed]
ΔG-scale:
Molecular code for transmembrane-helix recognition by the Sec61 translocon. Tara Hessa, Nadja Meindl-Beinker, Andreas Bernsel, Joy Kim, Yoko Sato, Mirjam Lerch, Carolina Lundin, IngMarie Nilsson, Stephen H. White, and Gunnar von Heijne (2007) Nature 450, 1026-1030. [PubMed]
ZPRED:
ZPRED: Predicting the distance to the membrane center for residues in alpha-helical membrane proteins. Erik Granseth, Håkan Viklund and Arne Elofsson (2006) Bioinformatics 22, e191-e196 [PubMed]
PRO/PRODIV-TMHMM:
Best alpha-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information. Håkan Viklund and Arne Elofsson (2004) Protein Science 13, 1908-1917 [PubMed]


 
5. Contact

Arne Elofsson group

Center for Biomembrane Research
Department for Biochemistry and Biophysics
The Arrhenius Laboratories for Natural Sciences
Stockholm University
SE-106 91 Stockholm, Sweden

E-mail:   arne@bioinfo.se
Phone:   (+46)-8-16 4672
Fax:   (+46)-8-15 3679



 
 
 
© 2008 Stockholm University, Stockholm Bioinformatics Center