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Major structural determinants of transmembrane proteins identified by principal component analysis
Author(s) -
Koshi Jeffrey M.,
Bruno William J.
Publication year - 1999
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/(sici)1097-0134(19990215)34:3<333::aid-prot6>3.0.co;2-2
Subject(s) - principal component analysis , transmembrane protein , computational biology , component (thermodynamics) , transmembrane domain , chemistry , biology , computer science , biochemistry , artificial intelligence , membrane , physics , thermodynamics , receptor
We identify amino acid characteristics important in determining the secondary structures of transmembrane proteins, and compare them with characteristics important for cytoplasmic proteins. Using information derived from multiple sequence alignments, we perform a principal component analysis (PCA) to identify the directions in the 20‐dimensional amino acid frequency space that comprise the most variance within each protein secondary structure. These vectors represent the important position‐specific properties of the amino acids for coils, turns, β sheets, and α helices. As expected, the most important axis for most of the datasets was hydrophobicity. Additional axes, distinct from hydrophobicity, are surprising, especially in the case of transmembrane α helices, where the effects of aromaticity and β‐branching are the next two most significant characteristics. The axis representing β‐branching also has equal importance in cytoplasmic and transmembrane helices, a finding that contrasts with some experimental results in membrane‐like environments. In a further analysis, we examine trends for some of the PCA axes over averaged transmembrane α helices, and find interesting results for aromaticity. Proteins 1999;34:333–340. Published 1999 Wiley‐Liss, Inc.