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MPRAP: An accessibility predictor for a-helicaltransmem-brane proteins that performs well insideand outside the membrane.
- Source :
-
BMC Bioinformatics . 2010, Vol. 11, p333-343. 11p. - Publication Year :
- 2010
-
Abstract
- Background: In water-soluble proteins it is energetically favorable to bury hydrophobic residues and to expose polar and charged residues. In contrast to water soluble proteins, transmembrane proteins face three distinct environments; a hydrophobic lipid environment inside the membrane, a hydrophilic water environment outside the membrane and an interface region rich in phospholipid head-groups. Therefore, it is energetically favorable for transmembrane proteins to expose different types of residues in the different regions. Results: Investigations of a set of structurally determined transmembrane proteins showed that the composition of solvent exposed residues differs significantly inside and outside the membrane. In contrast, residues buried within the interior of a protein show a much smaller difference. However, in all regions exposed residues are less conserved than buried residues. Further, we found that current state-of-the-art predictors for surface area are optimized for one of the regions and perform badly in the other regions. To circumvent this limitation we developed a new predictor, MPRAP, that performs well in all regions. In addition, MPRAP performs better on complete membrane proteins than a combination of specialized predictors and acceptably on water-soluble proteins. A web-server of MPRAP is available at http://mprap.cbr.su.se/ Conclusion: By including complete a-helical transmembrane proteins in the training MPRAP is able to predict surface accessibility accurately both inside and outside the membrane. This predictor can aid in the prediction of 3D-structure, and in the identification of erroneous protein structures. [ABSTRACT FROM AUTHOR]
- Subjects :
- *PROTEINS
*LIPIDS
*BIOMOLECULES
*BIOLOGICAL membranes
*MEMBRANE proteins
Subjects
Details
- Language :
- English
- ISSN :
- 14712105
- Volume :
- 11
- Database :
- Academic Search Index
- Journal :
- BMC Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 52802607
- Full Text :
- https://doi.org/10.1186/1471-2105-11-333