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

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


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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Amino Acid Transport Systems, Neutral / chemistry
  • Computational Biology / methods
  • Computer Simulation*
  • Databases, Protein
  • Escherichia coli Proteins / chemistry
  • Humans
  • Lactoferrin / chemistry
  • Models, Molecular
  • Motion
  • Protein Structure, Tertiary*
  • Sequence Analysis, Protein / methods*
  • Software


  • Amino Acid Transport Systems, Neutral
  • Escherichia coli Proteins
  • glnH protein, E coli
  • Lactoferrin