Information-driven Modelling of Biomolecular Complexes

Alexandre M.J.J. Bonvin
Utrecht University, The Netherlands

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 X-ray crystallography and NMR spectroscopy will not be sufficient to gain structural insight into those. A wealth of biochemical and/or biophysical data, such as SAXS, 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 constituents, should provide valuable structural information and complement the classical structural methods.

We have developed for this purpose a data-driven, semi-flexible docking approach called HADDOCK (High Ambiguity Driven protein-protein DOCKing) which is now also available as web server (www.haddocking.org). HADDOCK distinguishes itself from ab-initio docking methods in the fact that it encodes information from identified (e.g. via NMR, MS, mutagenesis,...) or predicted protein interfaces in ambiguous interaction restraints (AIRs) to drive the docking process. In addition, information on the relative orientation of the component of a complex can be included in the form of residual dipolar couplings or diffusion anisotropy restraints.

Flexibility is accounted for in different ways: in the initial docking phase by enabling docking from ensembles of starting conformations, and during the refinement stage by introducing explicit flexibility along side-chains and backbone of the interfacial regions. In that way, small to medium conformational changes taking place during complex formation can be modeled. Larger conformational changes could be modeled by dissecting the proteins in sub-fragment and performing a multi-body docking. HADDOCK currently supports up to 6 separate molecules and allow to impose various symmetry restraints in the case of symmetrical oligomers. Next to protein-protein complexes HADDOCK can also deal with protein-nucleic acids and protein-ligand complexes.

In my talk I will discuss the various sources of data that can be used to map interactions and illustrate their use in HADDOCK with examples from our laboratory. I will further illustrate how ab initio or data-driven docking and SAXS data can be combined to discriminate between solutions and/or refine rigid-body docking models from SAXS modelling.

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.

van Dijk ADJ, Boelens R and Bonvin AMJJ (2005). Data-driven docking for the study of biomolecular complexes. FEBS Journal, 272, 293-312.

van Dijk M, van Dijk ADJ, Hsu V, Kaptein R, Boelens R and Bonvin AMJJ (2006). Information-driven protein-DNA docking using HADDOCK: it is a matter of flexibility. Nucl. Acids Res., 34, 3317-3325.

A.D.J. van Dijk and A.M.J.J. Bonvin (2006). Solvated docking: introducing water into the modelling of biomolecular complexes. Bioinformatics, 22, 2340-2347.

de Vries SJ, van Dijk ADJ, Krzeminski,, M van Dijk M, Thureau A, Hsu V, Wassenaar T and Bonvin AMJJ (2007). HADDOCK versus HADDOCK: New features and performance of HADDOCK2.0 on the CAPRI targets. Proteins: Struc. Funct. & Bioinformatic, 69, 726-733.

de Vries SJ and Bonvin AMJJ (2008). How proteins get in touch: Interface prediction in the study of biomolecular complexes. Curr. Pept. and Prot. Research, 9, 394-406.

Date/time: Friday, 24 October, 14:45