DOI: 10.1093/bioinformatics/btl677. Improving the accuracy of transmembrane protein topology prediction using evolutionary information

Improving the accuracy of transmembrane protein topology prediction using evolutionary information

10.1093/bioinformatics/btl677

Crossref journal-article

Oxford University Press (OUP)

Bioinformatics (286)

Abstract

AbstractMotivation: Many important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell–cell communication, cell recognition and cell adhesion are mediated by membrane proteins. Unfortunately, as these proteins are not water soluble, it is extremely hard to experimentally determine their structure. Therefore, improved methods for predicting the structure of these proteins are vital in biological research. In order to improve transmembrane topology prediction, we evaluate the combined use of both integrated signal peptide prediction and evolutionary information in a single algorithm.Results: A new method (MEMSAT3) for predicting transmembrane protein topology from sequence profiles is described and benchmarked with full cross-validation on a standard data set of 184 transmembrane proteins. The method is found to predict both the correct topology and the locations of transmembrane segments for 80% of the test set. This compares with accuracies of 62–72% for other popular methods on the same benchmark. By using a second neural network specifically to discriminate transmembrane from globular proteins, a very low overall false positive rate (0.5%) can also be achieved in detecting transmembrane proteins.Availability: An implementation of the described method is available both as a web server (http://www.psipred.net) and as downloadable source code from http://bioinf.cs.ucl.ac.uk/memsat. Both the server and source code files are free to non-commercial users. Benchmark and training data are also available from http://bioinf.cs.ucl.ac.uk/memsat.Contact: dtj@cs.ucl.ac.uk

Bibliography

Jones, D. T. (2007). Improving the accuracy of transmembrane protein topology prediction using evolutionary information. Bioinformatics, 23(5), 538â544.

Authors 1

David T. Jones (first)

References 27 Referenced 358

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10.1093/nar/gkl208 / Nucl. Acids Res. by Amico (2006)
10.1038/nature04395 / Nature / Solving the membrane protein folding problem by Bowie (2005)
10.1093/nar/28.1.235 / Nucl. Acid Res / The Protein Data Bank by Berman (2000)
10.1038/nature04395 / Nature / Solving the membrane protein folding problem by Bowie (2005)
10.1110/ps.0214502 / Protein Sci. / Transmembrane helix predictions revisited by Chen (2002)
10.1002/pro.5560020106 / Protein Sci. / Modeling alpha-helical transmembrane domains: the calculation and use of substitution tables for lipid facing residues by Donnelly (1993)
10.1016/j.sbi.2006.06.003 / Curr. Opin. Struct. Biol. / Progress in structure prediction of α-helical membrane proteins by Fleishman (2006)
10.1016/S0022-2836(03)00182-7 / J. Mol. Biol. / Reliability measures for membrane protein topology prediction algorithms by Melen (2003)
10.1021/bi00176a037 / Biochemistry / A model recognition approach to the prediction of all-helical membrane protein structure and topology by Jones (1994)
10.1016/S0014-5793(98)00095-7 / FEBS Lett. / Do transmembrane protein superfolds exist? by Jones (1998)
10.1006/jmbi.1999.3091 / J. Mol. Biol. / Protein secondary structure prediction based on position-specific scoring matrices by Jones (1999)
10.1016/j.jmb.2004.03.016 / J. Mol. Biol. / A combined transmembrane topology and signal peptide prediction method by Käll (2004)
10.1093/bioinformatics/bti1014 / Bioinformatics / An HMM posterior decoder for sequence feature prediction that includes homology information by Käll (2005)
10.1016/0022-2836(82)90515-0 / J. Mol. Biol. / A simple method for displaying the hydropathic character of proteins by Kyte (1982)
10.1093/bioinformatics/btg1027 / Bioinformatics / An ENSEMBLE machine learning approach for the prediction of all-alpha membrane proteins by Martelli (2003)
10.1093/bioinformatics/17.7.646 / Bioinformatics / Evaluation of methods for the prediction of membrane spanning regions by Moller (2001)
10.1110/ps.0226702 / Prot. Sci. / Prediction of partial membrane protein topologies using a consensus approach by Nilsson (2002)
10.1002/pro.5560040318 / Prot. Sci. / Topology prediction for helical transmembrane proteins at 86% accuracy by Rost (1996)
{'key': '2023041109265416300_', 'first-page': '175', 'article-title': 'A hidden Markov model for predicting transmembrane helices in protein sequences', 'volume': '6', 'author': 'Sonnhammer', 'year': '1998', 'journal-title': 'Intell. Syst. Mol. Biol.'} / Intell. Syst. Mol. Biol. / A hidden Markov model for predicting transmembrane helices in protein sequences by Sonnhammer (1998)
10.1006/jmbi.1998.2107 / J. Mol. Bio. / Principles governing amino acid composition of integral membrane proteins: application to topology prediction by Tusnady (1998)
10.1002/prot.340180309 / Proteins / A method for alpha-helical integral membrane protein fold prediction by Taylor (1994)
10.1016/0022-2836(92)90934-C / J. Mol. Biol. / Membrane protein structure prediction by von Heijne (1992)
10.1002/pro.5560070420 / Prot. Sci. / Genome-wide analysis of integral membrane proteins from eubacterial, archaean, and eukaryotic organisms by Wallin (1998)
10.1146/annurev.biophys.28.1.319 / Ann. Rev. Biophys. Struct. / Membrane protein folding and stability: physical principles by White (1999)
10.1074/jbc.R100008200 / J. Biol. Chem. / How membranes shape protein structure by White (2001)
10.1002/prot.20817 / Proteins / Multipass membrane protein structure prediction using Rosetta by Yarov-Yarovoy (2006)

Dates

Type	When
Created	18 years, 7 months ago (Jan. 19, 2007, 8:12 p.m.)
Deposited	1 year, 6 months ago (Feb. 10, 2024, 4:42 a.m.)
Indexed	1 month ago (July 30, 2025, 10:30 a.m.)
Issued	18 years, 7 months ago (Jan. 19, 2007)
Published	18 years, 7 months ago (Jan. 19, 2007)
Published Online	18 years, 7 months ago (Jan. 19, 2007)
Published Print	18 years, 6 months ago (March 1, 2007)

Funders 0

None

BibTeX

@article{Jones_2007, title={Improving the accuracy of transmembrane protein topology prediction using evolutionary information}, volume={23}, ISSN={1367-4803}, url={http://dx.doi.org/10.1093/bioinformatics/btl677}, DOI={10.1093/bioinformatics/btl677}, number={5}, journal={Bioinformatics}, publisher={Oxford University Press (OUP)}, author={Jones, David T.}, year={2007}, month=jan, pages={538–544} }

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