Literature DB >> 19521654

Strong correlation between statistical transmembrane tendency and experimental hydrophobicity scales for identification of transmembrane helices.

Gang Zhao1, Erwin London.   

Abstract

Direct physical chemistry measurements of the hydrophobicity of amino acids or their derivatives have often been used to estimate the propensity of amino acids to participate in transmembrane helices. In this short note, it is found that there is a very high degree of correlation (r = 0.944-0.965) between an average physical chemistry hydrophobicity scale (an average of scales derived, e.g., from the solubility of amino acid derivatives in organic solvents versus water or their binding to hydrophobic particles) and the statistically based transmembrane tendency scale (derived from the relative abundance of residues in known transmembrane and soluble protein sequences (Zhao and London, Protein Sci 15:1987-2001, 2006)). This correlation indicates that, other than hydrophobicity, amino acid properties/interactions that promote or inhibit transmembrane helix formation in a specific membrane protein largely cancel out when averaged over all transmembrane sequences. In other words, other than hydrophobicity, there are no properties of a specific amino acid residue within a hydrophobic segment that have a strong systematic effect upon transmembrane helix formation independent of the remainder of the sequence in that hydrophobic segment. However, proline is an exception to this rule.

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Year:  2009        PMID: 19521654     DOI: 10.1007/s00232-009-9178-0

Source DB:  PubMed          Journal:  J Membr Biol        ISSN: 0022-2631            Impact factor:   1.843


  21 in total

1.  TM Finder: a prediction program for transmembrane protein segments using a combination of hydrophobicity and nonpolar phase helicity scales.

Authors:  C M Deber; C Wang; L P Liu; A S Prior; S Agrawal; B L Muskat; A J Cuticchia
Journal:  Protein Sci       Date:  2001-01       Impact factor: 6.725

2.  Development of hydrophobicity parameters to analyze proteins which bear post- or cotranslational modifications.

Authors:  S D Black; D R Mould
Journal:  Anal Biochem       Date:  1991-02-15       Impact factor: 3.365

3.  An improved hidden Markov model for transmembrane protein detection and topology prediction and its applications to complete genomes.

Authors:  Robel Y Kahsay; Guang Gao; Li Liao
Journal:  Bioinformatics       Date:  2005-02-02       Impact factor: 6.937

4.  An amino acid "transmembrane tendency" scale that approaches the theoretical limit to accuracy for prediction of transmembrane helices: relationship to biological hydrophobicity.

Authors:  Gang Zhao; Erwin London
Journal:  Protein Sci       Date:  2006-08       Impact factor: 6.725

5.  Molecular code for transmembrane-helix recognition by the Sec61 translocon.

Authors:  Tara Hessa; Nadja M Meindl-Beinker; Andreas Bernsel; Hyun Kim; Yoko Sato; Mirjam Lerch-Bader; IngMarie Nilsson; Stephen H White; Gunnar von Heijne
Journal:  Nature       Date:  2007-12-13       Impact factor: 49.962

6.  New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites.

Authors:  J M Parker; D Guo; R S Hodges
Journal:  Biochemistry       Date:  1986-09-23       Impact factor: 3.162

Review 7.  Experimentally determined hydrophobicity scale for proteins at membrane interfaces.

Authors:  W C Wimley; S H White
Journal:  Nat Struct Biol       Date:  1996-10

8.  Hydrophilicity of polar amino acid side-chains is markedly reduced by flanking peptide bonds.

Authors:  M A Roseman
Journal:  J Mol Biol       Date:  1988-04-05       Impact factor: 5.469

9.  Surface tension of amino acid solutions: a hydrophobicity scale of the amino acid residues.

Authors:  H B Bull; K Breese
Journal:  Arch Biochem Biophys       Date:  1974-04-02       Impact factor: 4.013

10.  A simple method for displaying the hydropathic character of a protein.

Authors:  J Kyte; R F Doolittle
Journal:  J Mol Biol       Date:  1982-05-05       Impact factor: 5.469

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Authors:  Irina D Pogozheva; Henry I Mosberg; Andrei L Lomize
Journal:  Protein Sci       Date:  2014-07-02       Impact factor: 6.725

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3.  Sequence signatures of direct complementarity between mRNAs and cognate proteins on multiple levels.

Authors:  Mario Hlevnjak; Anton A Polyansky; Bojan Zagrovic
Journal:  Nucleic Acids Res       Date:  2012-07-25       Impact factor: 16.971

4.  In silico evaluation of the influence of the translocon on partitioning of membrane segments.

Authors:  Dominique Tessier; Sami Laroum; Béatrice Duval; Emma M Rath; W Bret Church; Jin-Kao Hao
Journal:  BMC Bioinformatics       Date:  2014-05-21       Impact factor: 3.169

  4 in total

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