Journal
JOURNAL OF MOLECULAR BIOLOGY
Volume 305, Issue 3, Pages 567-580Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1006/jmbi.2000.4315
Keywords
transmembrane helices; hidden Markov model; prediction of membrane protein topology; membrane proteins in genomes; protein structure prediction
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We describe and validate a new membrane protein topology prediction method, TMHMM, based on a hidden Markov model. We present a detailed analysis of TMHMM's performance, and show that it correctly predicts 97-98% of the transmembrane helices. Additionally, TMHMM can discriminate between soluble and membrane proteins with both specificity and sensitivity better than 99 %, although the accuracy drops when signal peptides are present. This high degree of accuracy allowed us to predict reliably integral membrane proteins in a large collection of genomes. Based on these predictions, we estimate that 20-30% of all genes in most genomes encode membrane proteins, which is in agreement with previous estimates. We further discovered that proteins with N-in-C-in topologies are strongly preferred in all examined organisms, except Caenorhabditis elegans, where the large number of 7TM receptors increases the counts for N-out-C-in topologies. We discuss the possible relevance of this finding for our understanding of membrane protein assembly mechanisms. A TMHMM prediction service is available at http://www.cbs.dtu.dk/services/TMHMM/. (C) 2001 Academic Press.
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