Article
Received: 14 August 2008; Revised: 12 November 2008; Accepted: 17 November 2008
10.1002/pro.38 About DOI
StoneHinge: Hinge prediction by network analysis of individual protein structures |
| Kevin S. Keating 1, Samuel C. Flores 2 3 a, Mark B. Gerstein 1 3 4, Leslie A. Kuhn 5 6 7 * |
| 1Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 2Department of Physics, Yale University, New Haven, Connecticut 3Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 4Department of Computer Science, Yale University, New Haven, Connecticut 5Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 6Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan 7Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan |
| email: Samuel C. Flores (samuel.flores@aya.yale.edu) Leslie A. Kuhn (kuhnl@msu.edu) |
*Correspondence to Leslie A. Kuhn, Protein Structural Analysis and Design Lab, 502C Biochemistry Building, Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824-1319
aCurrent address: James H. Clark Center S231, MC 5448, Stanford University, Stanford, California
Funded by:
NIH; Grant Number: GM 72970, GM 67249, AI 53877, T15 LM07056 Keck Foundation: AL Williams Professorship Funds Simbios NIH Roadmap for Medical Research; Grant Number: U54 GM072970
| Keywords |
| hinge bending conformational change flexibility rigidity theory ProFlex FIRST DomDecomp domain identification |
| Abstract |
| Hinge motions are important for molecular recognition, and knowledge of their location can guide the sampling of protein conformations for docking. Predicting domains and intervening hinges is also important for identifying structurally self-determinate units and anticipating the influence of mutations on protein flexibility and stability. Here we present StoneHinge, a novel approach for predicting hinges between domains using input from two complementary analyses of noncovalent bond networks: StoneHingeP, which identifies domain-hinge-domain signatures in ProFlex constraint counting results, and StoneHingeD, which does the same for DomDecomp Gaussian network analyses. Predictions for the two methods are compared to hinges defined in the literature and by visual inspection of interpolated motions between conformations in a series of proteins. For StoneHingeP, all the predicted hinges agree with hinge sites reported in the literature or observed visually, although some predictions include extra residues. Furthermore, no hinges are predicted in six hinge-free proteins. On the other hand, StoneHingeD tends to overpredict the number of hinges, while accurately pinpointing hinge locations. By determining the consensus of their results, StoneHinge improves the specificity, predicting 11 of 13 hinges found both visually and in the literature for nine different open protein structures, and making no false-positive predictions. By comparison, a popular hinge detection method that requires knowledge of both the open and closed conformations finds 10 of the 13 known hinges, while predicting four additional, false hinges. |
Received: 14 August 2008; Revised: 12 November 2008; Accepted: 17 November 2008
| Digital Object Identifier (DOI) |
10.1002/pro.38 About DOI
