Prediction of functionally important residues in globular proteins from unusual central distances of amino acids.

ABSTRACT:

Background

Well-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues.

Results

Using a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under considerati

SUBMITTER: Kochanczyk M 

PROVIDER: S-EPMC3188475 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature