The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2.

Computational docking is the prediction or modeling of the three-dimensional structure of a biomolecular complex, starting from the structures of the individual molecules in their free, unbound form. HADDOCK is a popular docking program that takes a data-driven approach to docking, with support for a wide range of experimental data. Here we present the HADDOCK web server protocol, facilitating the modeling of biomolecular complexes for a wide community. The main web interface is user-friendly, requiring only the structures of the individual components and a list of interacting residues as input. Additional web interfaces allow the more advanced user to exploit the full range of experimental data supported by HADDOCK and to customize the docking process. The HADDOCK server has access to the resources of a dedicated cluster and of the e-NMR GRID infrastructure. Therefore, a typical docking run takes only a few minutes to prepare and a few hours to complete.

There is a growing interest in structural studies of DNA by both experimental and computational approaches. Often, 3D-structural models of DNA are required, for instance, to serve as templates for homology modeling, as starting structures for macro-molecular docking or as scaffold for NMR structure calculations. The conformational adaptability of DNA when binding to a protein is often an important factor and at the same time a limitation in such studies. As a response to the demand for 3D-structural models reflecting the intrinsic plasticity of DNA we present the 3D-DART server (3DNA-Driven DNA Analysis and Rebuilding Tool). The server provides an easy interface to a powerful collection of tools for the generation of DNA-structural models in custom conformations. The computational engine beyond the server makes use of the 3DNA software suite together with a collection of home-written python scripts. The server is freely available at http://haddock.chem.uu.nl/dna without any login requirement.

The WeNMR (http://www.wenmr.eu) project is an EU-funded international effort to streamline and automate structure determination from Nuclear Magnetic Resonance (NMR) data. Conventionally calculation of structure requires the use of various softwares, considerable user expertise and ample computational resources. To facilitate the use of NMR spectroscopy in life sciences the eNMR/WeNMR consortium has set out to provide protocolized services through easy-to-use web interfaces, while still retaining sufficient flexibility to handle more specific requests. Thus far, a

Intrinsic flexibility of DNA has hampered the development of efficient protein−DNA docking methods. In this study we extend HADDOCK (High Ambiguity Driven DOCKing) [C. Dominguez, R. Boelens and A. M. J. J. Bonvin (2003) J. Am. Chem. Soc. 125, 1731–1737] to explicitly deal with DNA flexibility. HADDOCK uses non-structural experimental data to drive the docking during a rigid-body energy minimization, and semi-flexible and water refinement stages. The latter allow for flexibility of all DNA nucleotides and the residues of the protein at the predicted interface. We evaluated our approach on the monomeric repressor−DNA complexes formed by bacteriophage 434 Cro, the Escherichia coli Lac headpiece and bacteriophage P22 Arc. Starting from unbound proteins and canonical B-DNA we correctly predict the correct spatial disposition of the complexes and the specific conformation of the DNA in the published complexes. This information is subsequently used to generate a library of pre-bent and twisted DNA structures that served as input for a second docking round. The resulting top ranking solutions exhibit high similarity to the published complexes in terms of root mean square deviations, intermolecular contacts and DNA conformation. Our two-stage docking method is thus able to successfully predict protein−DNA complexes from unbound constituents using non-structural experimental data to drive the docking.

SUMMARY The integration of biophysical data from multiple sources is critical for developing accurate structural models of large multiprotein systems and their regulators. Mass spectrometry (MS) can be used to measure the insertion location for a wide range of topographically sensitive chemical probes, and such insertion data provide a rich, but disparate set of modeling restraints. We have developed a software platform that integrates the analysis of label-based MS data with protein modeling activities (Mass Spec Studio). Analysis packages can mine any labeling data from any mass spectrometer in a proteomics-grade manner, and link labeling methods with data-directed protein interaction modeling using HADDOCK. Support is provided for hydrogen/ deuterium exchange (HX) and covalent labeling chemistries, including novel acquisition strategies such as targeted HX-tandem MS (MS2) and data-independent HX-MS2. The latter permits the modeling of highly complex systems, which we demonstrate by the analysis of microtubule interactions.

We present a protein–DNA docking benchmark containing 47 unbound–unbound test cases of which 13 are classified as easy, 22 as intermediate and 12 as difficult cases. The latter shows considerable structural rearrangement upon complex formation. DNA-specific modifications such as flipped out bases and base modifications are included. The benchmark covers all major groups of DNA-binding proteins according to the classification of Luscombe et al., except for the zipper-type group. The variety in test cases make this non-redundant benchmark a useful tool for comparison and development of protein–DNA docking methods. The benchmark is freely available as download from the internet.

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