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Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices
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 m...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2004
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC516255/ https://www.ncbi.nlm.nih.gov/pubmed/15312230 http://dx.doi.org/10.1186/1742-4682-1-5 |
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author | Wallace, James Daman, Onkabetse A Harris, Frederick Phoenix, David A |
author_facet | Wallace, James Daman, Onkabetse A Harris, Frederick Phoenix, David A |
author_sort | Wallace, James |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-516255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-5162552004-09-09 Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices Wallace, James Daman, Onkabetse A Harris, Frederick Phoenix, David A Theor Biol Med Model Research 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. BioMed Central 2004-08-16 /pmc/articles/PMC516255/ /pubmed/15312230 http://dx.doi.org/10.1186/1742-4682-1-5 Text en Copyright © 2004 Wallace et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Wallace, James Daman, Onkabetse A Harris, Frederick Phoenix, David A Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
title | Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
title_full | Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
title_fullStr | Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
title_full_unstemmed | Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
title_short | Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
title_sort | investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC516255/ https://www.ncbi.nlm.nih.gov/pubmed/15312230 http://dx.doi.org/10.1186/1742-4682-1-5 |
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