Abstract
Integral membrane proteins are the primary targets of novel drugs but are largely without solved structures. As a consequence, hydrophobic moment plot methodology is often used to identify putative transmembrane α-helices of integral membrane proteins, based on their local maximum mean hydrophobic moment (<μH>) and the corresponding mean hydrophobicity (<H>). To calculate these properties, the methodology identifies an optimal eleven residue window (L = 11), assuming an amino acid angular frequency, θ, fixed at 100°.Using a data set of 403 transmembrane α-helix forming sequences, the relationship between <μH> and <H>, and the effect of varying of L and / or θ on this relationship, was investigated. Confidence intervals for correlations between <μH> and <H> are established. It is shown, using bootstrapping procedures that the strongest statistically significant correlations exist for small windows where 7 ≤ L ≤ 16. Monte Carlo analysis suggests that this correlation is dependent upon amino acid residue primary structure, implying biological function and indicating that smaller values of L give better characterisation of transmembrane sequences using <μH>. However, varying window size can also lead to different regions within a given sequence being identified as the optimal window for structure / function predictions. Furthermore, it is shown that optimal periodicity varies with window size; the optimum, based on <μH> over the range of window sizes, (7 ≤ L ≤ 16), was at θ = 102° for the transmembrane α-helix data set.
Highlights
Integral membrane proteins are the primary choice as targets when developing new drugs and clearly of medical relevance, forming 20% – 30% of the gene products of most genomes, these proteins have been structurally determined in only about thirty cases [1,2]
A number of αhelical properties have been used as models to study transmembrane α-helices and their structure / function relationships but the most commonly used are those based on the amphiphilicity of protein α-helices with the hydrophobic moment used as a measure of amphiphilicity [3]
For the sequences of this data set, the maximum mean hydrophobic moment, , and its corresponding mean hydrophobicity, , were determined and used to generate the hydrophobic moment plot shown in figure 1, based on the generally used 11 residue window (L = 11) introduced by Eisenberg et al, [4]
Summary
Integral membrane proteins are the primary choice as targets when developing new drugs and clearly of medical relevance, forming 20% – 30% of the gene products of most genomes, these proteins have been structurally determined in only about thirty cases [1,2]. Theoretical Biology and Medical Modelling 2004, 1:5 http://www.tbiomed.com/content/1/1/5 sequence information alone is available, the identification of transmembrane α-helical structure requires a bioinformatics approach to understanding the structure / function relationships of these α-helices. A number of αhelical properties have been used as models to study transmembrane α-helices and their structure / function relationships but the most commonly used are those based on the amphiphilicity of protein α-helices with the hydrophobic moment used as a measure of amphiphilicity [3]. For a structure comprising L consecutive residues, the general form of μ(θ) is given by: L
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