Co-evolving residues in membrane proteins
Open Access
- 15 December 2007
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 23 (24) , 3312-3319
- https://doi.org/10.1093/bioinformatics/btm515
Abstract
Motivation: The analysis of co-evolving residues has been exhaustively evaluated for the prediction of intramolecular amino acid contacts in soluble proteins. Although a variety of different methods for the detection of these co-evolving residues have been developed, the fraction of correctly predicted contacts remained insufficient for their reliable application in the construction of structural models. Membrane proteins, which constitute between one-fourth and one-third of all proteins in an organism, were only considered in few individual case studies. Results: We present the first general study of correlated mutations in α-helical membrane proteins. Using seven different prediction algorithms, we extracted co-evolving residues for 14 membrane proteins having a solved 3D structure. On average, distances between correlated pairs of residues lying on different transmembrane segments were found to be significantly smaller compared to a random prediction. Covariation of residues was frequently found in direct sequence neighborhood to helix–helix contacts. Based on the results obtained from individual prediction methods, we constructed a consensus prediction for every protein in the dataset that combines obtained correlations from different prediction algorithms and simultaneously removes likely false positives. Using this consensus prediction, 53% of all predicted residue pairs were found within one helix turn of an observed helix–helix contact. Based on the combination of co-evolving residues detected with the four best prediction algorithms, interacting helices could be predicted with a specificity of 83% and sensitivity of 42%. Availability:http://webclu.bio.wzw.tum.de/helixcorr/ Contact:d.frishman@wzw.tum.de Supplementary information: Supplementary data are available at Bioinformatics online.Keywords
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