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Proteins. 2008 Nov 1;73(2):299-319. doi: 10.1002/prot.22060.

HingeMaster: normal mode hinge prediction approach and integration of complementary predictors.

Author information

1
Department of Physics, Yale University, New Haven, Connecticut 06520, USA. samuel.flores@aya.yale.edu

Abstract

Protein motion is often the link between structure and function and a substantial fraction of proteins move through a domain hinge bending mechanism. Predicting the location of the hinge from a single structure is thus a logical first step towards predicting motion. Here, we describe ways to predict the hinge location by grouping residues with correlated normal-mode motions. We benchmarked our normal-mode based predictor against a gold standard set of carefully annotated hinge locations taken from the Database of Macromolecular Motions. We then compared it with three existing structure-based hinge predictors (TLSMD, StoneHinge, and FlexOracle), plus HingeSeq, a sequence-based hinge predictor. Each of these methods predicts hinges using very different sources of information-normal modes, experimental thermal factors, bond constraint networks, energetics, and sequence, respectively. Thus it is logical that using these algorithms together would improve predictions. We integrated all the methods into a combined predictor using a weighted voting scheme. Finally, we encapsulated all our results in a web tool which can be used to run all the predictors on submitted proteins and visualize the results.

PMID:
18433058
DOI:
10.1002/prot.22060
[Indexed for MEDLINE]

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