z-logo
Premium
A consensus procedure improving solvent accessibility prediction
Author(s) -
Gianese Giulio,
Pascarella Stefano
Publication year - 2006
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.20370
Subject(s) - computer science , construct (python library) , data mining , machine learning , programming language
Prediction methods of structural features in 1D represent a useful tool for the understanding of folding, classification, and function of proteins, and, in particular, for 3D structure prediction. Among the structural aspects characterizing a protein, solvent accessibility has received great attention in recent years. The available methods proposed for predicting accessibility have never considered the combination of the results deriving from different methods to construct a consensus prediction able to provide more reliable results. A consensus approach that increases prediction accuracy using three high‐performance methods is described. The results of our method for three different protein data sets show that up to 3.0% improvement in prediction accuracy of solvent accessibility may be obtained by a consensus approach. The improvement also extends to the correlation coefficient. Application of our consensus approach to the accessibility prediction using only three prediction methods gives results better than single methods combined for consensus formation. Currently, the scarce availability of predictors with similar parameters defining solvent accessibility hinders the testing of other methods in our consensus procedure. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 621–626, 2006

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here