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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Influence of assignment on the prediction of transmembrane helices in protein structures
Jean Pylouster1, Aurélie Bornot, Catherine Etchebest
1INSERM UMR-S 726, Equipe de Bioinformatique Génomique et Moléculaire (EBGM), DSIMB, Université Paris Diderot-Paris 7, case 7113, 2, place Jussieu, 75251, Paris, France.
Abstract:
α-Helical transmembrane proteins (TMPα) are composed of a series of helices embedded in the lipid bilayer. Due to technical difficulties, few 3D structures are available. Therefore, the design of structural models of TMPα is of major interest. We study the secondary structures of TMPα by analyzing the influence of secondary structures assignment methods (SSAMs). For this purpose, a published and updated benchmark databank of TMPα is used and several SSAMs (9) are evaluated. The analysis of the results points to significant differences in SSA depending on the methods used. Pairwise comparisons between SSAMs led to more than 10% of disagreement. Helical regions corresponding to transmembrane zones are often correctly characterized. The study of the sequence-structure relationship shows very limited differences with regard to the structural disagreement. Secondary structure prediction based on Bayes' rule and using only a single sequence give correct prediction rates ranging from 78 to 81%. A structural alphabet approach gives a slightly better prediction, i.e., only 2% less than the best equivalent approach, whereas the prediction rate with a very different assignment bypasses 86%. This last result highlights the importance of the correct assignment choice to evaluate the prediction assessment.
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