Principles governing amino acid composition of integral membrane proteins: Application to topology prediction

被引:911
作者
Tusnady, GE [1 ]
Simon, I [1 ]
机构
[1] Hungarian Acad Sci, Inst Enzymol, Biol Res Ctr, H-1518 Budapest, Hungary
基金
匈牙利科学研究基金会;
关键词
hidden Markov model; transmembrane alpha-helices; topology prediction for helical transmembrane proteins; distribution of amino acids;
D O I
10.1006/jmbi.1998.2107
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A new method is suggested here for topology prediction of helical transmembrane proteins. The method is based on the hypothesis that the localizations of the transmembrane segments and the topology are determined by the difference in the amino acid distributions in various structural parts of these proteins rather than by specific amino acid compositions of these parts. A hidden Markov model with special architecture was developed to search transmembrane topology corresponding to the maximum likelihood among all the possible topologies of a given protein. The prediction accuracy was tested on 158 proteins and was found to be higher than that found using prediction methods already available. The method successfully predicted all the transmembrane segments in 143 proteins out of the 158, and for 135 of these proteins both the membrane spanning regions and the topologies were predicted correctly. The observed level of accuracy is a strong argument in favor of our hypothesis. (C) 1998 Academic Press.
引用
收藏
页码:489 / 506
页数:18
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