Encyclopedia of Biophysics

Living Edition
| Editors: Gordon Roberts, Anthony Watts, European Biophysical Societies

HADDOCK

  • Alexandre M. J. J. BonvinEmail author
  • C. Geng
  • M. van Dijk
  • E. Karaca
  • P. L. Kastritis
  • P. I. Koukos
  • Z. Kurkcuoglu
  • A. S. J. Melquiond
  • J. P. G. L. M. Rogridues
  • J. Schaarschmidt
  • C. Schmitz
  • J. Roel-Touris
  • M. E. Trellet
  • S. de Vries
  • A. Vangone
  • L. Xue
  • G. C. P. van Zundert
Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-35943-9_330-1
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Definition

HADDOCK (High Ambiguity Driven biomolecular DOCKing) is an information-driven flexible docking approach for the modeling of biomolecular complexes (Dominguez et al. 2003). Docking is defined as the modeling of the structure of a complex based on the known three-dimensional structures of its constituents. HADDOCK distinguishes itself from other docking methods by incorporating a wide variety of experimental and/or bioinformatics data to drive the modeling (Melquiond and Bonvin 2010; Rodrigues and Bonvin 2014). This allows concentrating the search to relevant portions of the interaction space using a more sophisticated treatment of conformational flexibility.

Interface regions can be identified by mutagenesis, H/D exchange, and chemical modifications (e.g., by cross-linkers or oxidative agents) detected by mass spectrometry, nuclear magnetic resonance, chemical shift perturbations, and cross-saturation transfer (see Fig. 1). When experimental data are unavailable or scarce, this information can be supplemented by bioinformatics predictions (de Vries and Bonvin 2008). These diverse information sources typically only identify or predict interfacial regions, but do not define the contacts across an interface. HADDOCK deals with this by implementing them as ambiguous interaction restraints (AIRs) that will force the interfaces to come together without imposing a particular orientation.
Fig. 1

HADDOCK can use a variety of experimental or predicted information to drive the modeling of biomolecular complexes. The most recent developments added the support for cryo-electron microscopy data in HADDOCK

HADDOCK can also incorporate classical NMR restraints such as distances from nuclear Overhauser effects and paramagnetic relaxation enhancement measurements, pseudo-contact shift, dihedral angles, residual dipolar coupling, and diffusion anisotropy restraints, the latter two providing valuable information about the relative orientation of the components in a complex. In addition, symmetry restraints can be defined in the case of symmetrical homomeric systems (Karaca et al. 2010). Other valuable information can be obtained from low-to-medium-resolution techniques such as small-angle X-ray scattering (Karaca and Bonvin 2013), cryo-electron microscopy (van Zundert et al. 2015), and ion mobility-mass spectrometry that can provide valuable information about the shape of a complex.

The docking protocol in HADDOCK, which makes use of the crystallography and NMR system (CNS) package as computational engine, consists of three successive steps: (a) rigid-body energy minimization, (b) semiflexible refinement in torsion angle space, and (c) final refinement in explicit solvent refinement. By allowing for explicit flexibility during the molecular dynamics refinement, HADDOCK can account for small conformational changes occurring upon binding. Larger and more challenging conformational changes can be dealt with by starting the docking from ensembles of conformations and/or treating the molecules as a collection of domains. The latter approach makes use of the unique multi-body docking ability of HADDOCK, which can handle up to 20 separate domains or molecules at the same time. The selection of the final models is based on a weighted sum of electrostatics, desolvation, and van der Waals energy terms, along with the energetic contribution of the restraints used to drive the docking.

HADDOCK has been extensively applied to a large variety of systems, including protein-protein, protein-nucleic acids, protein-peptide, and protein-small-molecule docking, and has shown a very strong performance in the blind critical assessment of the prediction of interactions (CAPRI). A considerable number of experimental structures of complexes calculated using HADDOCK have been deposited into the Protein Data Bank (PDB). HADDOCK is available as a web server (http://haddock.science.uu.nl/services/HADDOCK2.2) (van Zundert et al. 2016) offering a user-friendly interface to the structural biology community.

Cross-References

References

  1. de Vries S, Bonvin AMJJ (2008) How proteins get in touch: interface prediction in the study of biomolecular complexes. Curr Pept Prot Res 9:394–406CrossRefGoogle Scholar
  2. Dominguez C, Boelens R, Bonvin AMJJ (2003) HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J Am Chem Soc 125:1731–1737CrossRefPubMedGoogle Scholar
  3. Karaca E, Bonvin AMJJ (2013) On the usefulness of Ion Mobility Mass Spectrometry and SAXS data in scoring docking decoys. Acta Cryst D D69:683–694CrossRefGoogle Scholar
  4. Karaca E, Melquiond ASJ, de Vries SJ, Kastritis PL, Bonvin AMJJ (2010) Building macromolecular assemblies by information-driven docking: introducing the HADDOCK multi-body docking server. Mol Cell Proteomics 9:1784–1794CrossRefPubMedPubMedCentralGoogle Scholar
  5. Melquiond ASJ, Bonvin AMJJ (2010) Data-driven docking: using external information to spark the biomolecular rendez-vous. In: Zacharrias M (ed) Protein-protein complexes: analysis, modeling and drug design. Imperial College Press, London, pp 183–209Google Scholar
  6. Rodrigues JPGLM, Bonvin AMJJ (2014) Integrative computational modeling of protein interactions. FEBS J 281:1988–2003CrossRefPubMedGoogle Scholar
  7. van Zundert GCP, Melquiond ASJ, Bonvin AMJJ (2015) Integrative modeling of biomolecular complexes: HADDOCKing with Cryo-EM data. Structure 23:949–996CrossRefPubMedGoogle Scholar
  8. van Zundert GCP, Rodrigues JPGLM, Trellet ME, Schmitz C, Kastritis PL, Karaca E, Melquiond SJ, van Dijk M, de Vries SJ, Bonvin AMJJ (2016) The HADDOCK2.2 webserver: user-friendly integrative modeling of biomolecular complexes. J Mol Biol 428:720–725CrossRefPubMedGoogle Scholar

Copyright information

© European Biophysical Societies' Association (EBSA) 2018

Authors and Affiliations

  • Alexandre M. J. J. Bonvin
    • 1
    Email author
  • C. Geng
    • 1
  • M. van Dijk
    • 1
  • E. Karaca
    • 1
  • P. L. Kastritis
    • 1
  • P. I. Koukos
    • 1
  • Z. Kurkcuoglu
    • 1
  • A. S. J. Melquiond
    • 1
  • J. P. G. L. M. Rogridues
    • 1
  • J. Schaarschmidt
    • 1
  • C. Schmitz
    • 1
  • J. Roel-Touris
    • 1
  • M. E. Trellet
    • 1
  • S. de Vries
    • 1
  • A. Vangone
    • 1
  • L. Xue
    • 1
  • G. C. P. van Zundert
    • 1
  1. 1.Bijvoet Center for Biomolecular Research, Faculty of ScienceUtrecht UniversityUtrechtThe Netherlands

Section editors and affiliations

  • Mitsu Ikura

There are no affiliations available