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Protein-protein recognition: exploring the energy funnels near the binding sites

  1. Chao Zhang†,
  2. Jing Chen,
  3. Charles DeLisi*

Article first published online: 1 OCT 1999

DOI: 10.1002/(SICI)1097-0134(19990201)34:2<255::AID-PROT10>3.0.CO;2-O

Issue

Proteins: Structure, Function, and Bioinformatics

Proteins: Structure, Function, and Bioinformatics

Volume 34, Issue 2, pages 255–267, 1 February 1999

Additional Information

How to Cite

Zhang, C., Chen, J. and DeLisi, C. (1999), Protein-protein recognition: exploring the energy funnels near the binding sites. Proteins: Structure, Function, and Bioinformatics, 34: 255–267. doi: 10.1002/(SICI)1097-0134(19990201)34:2<255::AID-PROT10>3.0.CO;2-O

Author Information

  1. Department of Biomedical Engineering, Boston University College of Engineering, Boston, Massachusetts

  1. †

    220 Calvin Laboratory, University of California, Berkeley, CA 94720-5230.

*Boston University College of Engineering, 44 Cummington Street, Boston, MA 02215.

Publication History

  1. Issue published online: 1 OCT 1999
  2. Article first published online: 1 OCT 1999
  3. Manuscript Accepted: 1 OCT 1998
  4. Manuscript Received: 7 JUL 1998

Funded by

  • U.S. Department of Energy. Grant Number: DE-F602-96ER62263

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Keywords:

  • protein docking;
  • binding energy;
  • rate constant for protein-protein association;
  • percentage of native contacts;
  • structure-derived atomic contact energies

Abstract

We present a rapidly executable minimal binding energy model for molecular docking and use it to explore the energy landscape in the vicinity of the binding sites of four different enzyme inhibitor complexes. The structures of the complexes are calculated starting with the crystal structures of the free monomers, using DOCK 4.0 to generate a large number of potential configurations, and screening with the binding energy target function. In order to investigate possible correlations between energy and variation from the native structure, we introduce a new measure of similarity, which removes many of the difficulties associated with root mean square deviation. The analysis uncovers energy gradients, or funnels, near the binding site, with decreasing energy as the degree of similarity between the native and docked structures increases. Such energy funnels can increase the number of random collisions that may evolve into productive stable complex, and indicate that short-range interactions in the precomplexes can contribute to the association rate. The finding could provide an explanation for the relatively rapid association rates that are observed even in the absence of long-range electrostatic steering. Proteins 1999; 34:255–267. © 1999 Wiley-Liss, Inc.

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