Journal
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Volume 83, Issue 3, Pages 473-484Publisher
WILEY
DOI: 10.1002/prot.24749
Keywords
membrane protein; transmembrane helices; transmembrane helix; -helical membrane protein; transmembrane helix prediction; evaluation
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Funding
- Alexander von Humboldt foundation through German Federal Ministry for Education and Research (BMBF)
- New York Consortium on Membrane Protein Structure (NYCOMPS) from the Protein Structure Initiative (PSI) of the National Institutes of Health (NIH) [U54 GM095315]
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Experimental structure determination continues to be challenging for membrane proteins. Computational prediction methods are therefore needed and widely used to supplement experimental data. Here, we re-examined the state of the art in transmembrane helix prediction based on a nonredundant dataset with 190 high-resolution structures. Analyzing 12 widely-used and well-known methods using a stringent performance measure, we largely confirmed the expected high level of performance. On the other hand, all methods performed worse for proteins that could not have been used for development. A few results stood out: First, all methods predicted proteins in eukaryotes better than those in bacteria. Second, methods worked less well for proteins with many transmembrane helices. Third, most methods correctly discriminated between soluble and transmembrane proteins. However, several older methods often mistook signal peptides for transmembrane helices. Some newer methods have overcome this shortcoming. In our hands, PolyPhobius and MEMSAT-SVM outperformed other methods. Proteins 2015; 83:473-484. (c) 2014 Wiley Periodicals, Inc.
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