Download Data-driven docking for the study of biomolecular complexes

Information-driven modelling of biomolecular complexes.
Challenges and perspectives
Alexandre M. J. J. Bonvin
Computational Structural Biology, Bijvoet Center for Biomolecular Research, Faculty of Science,
Utrecht University, 3584CH, Utrecht, The Netherlands. Email: [email protected]
With the presently available amount of genetic information, a lot of attention focuses on systems
biology and in particular on biomolecular interactions. Considering the huge number of such
interactions, and their often weak and transient nature, conventional experimental methods such as Xray crystallography and NMR spectroscopy will not be sufficient to gain structural insight into those. A
wealth of biochemical and/or biophysical data can however easily be obtained for biomolecular
complexes. Combining these data with docking, the process of modeling the 3D structure of a complex
from its known components, should provide valuable structural information and complement the
classical structural methods.
We have developed for this purpose a data-driven docking approach called HADDOCK (High
Ambiguity Driven protein–protein DOCKing) (http://www.nmr.chem.uu.nl/haddock), which is now also
available as web server (http://www.haddocking.org/). HADDOCK distinguishes itself from ab-initio
docking methods in the fact that it encodes information from identified or predicted protein interfaces in
ambiguous interaction restraints (AIRs) to drive the docking process. Flexibility is accounted for in
different ways during the docking, which allows to model (small) conformational changes taking place
during complex formation.
In my talk I will present the current status of HADDOCK development and illustrate it with
examples from our laboratory together with results from our participation to the blind docking
experiment CAPRI (Critical Assessment of PRedicted Interactions) (http://capri.ebi.ac.uk). Finally I will
discuss some of the still open challenges in this field.
References:
Dominguez C, Boelens R and Bonvin AMJJ (2003). HADDOCK: A protein-protein docking approach based on biochemical
or biophysical information. J Am Chem Soc 125 1731-1737.
de Vries SJ and Bonvin AMJJ (2008). How proteins get in touch: Interface prediction in the study of biomolecular
complexes. Curr. Pept. Prot. Research 9, 394-406.
de Vries SJ, van Dijk, M and Bonvin AMJJ (2010). The HADDOCK server for data-driven biomolecular docking. Nature
Protocols 5, 883-897.
de Vries, SJ, Melquiond ASJ, Kastritis PL, Karaca E, Bordogna A, van Dijk M, Rodrigues JPGLM. and Bonvin AMJJ
(2010). Strengths and weaknesses of data-driven docking in CAPRI. Proteins: Struc. Funct. & Bioinformatic 78,
3242-3249 (2010).
Karaca E, Melquiond, ASJ, de Vries SJ, Kastritis PL and Bonvin AMJJ (2010). Building macromolecular assemblies by
information-driven docking: Introducing the HADDOCK multi-body docking server. Mol. Cell. Proteomics 9,
1784-1794.
van Dijk M and Bonvin AMJJ (2010). Pushing the limits of what is achievable in protein-DNA docking. Benchmarking
HADDOCK's performance. Nucl. Acid Res. 38, 5634-5647.
Kastritis PL and Bonvin AMJJ (2010). Are scoring functions in protein-protein docking ready to predict interactomes? Clues
from a novel binding affinity benchmark. J. Proteome Research, 9, 2216-2225.