Biomedical subjects

Aalt D J van Dijk

Publications and source records attributed to Aalt D J van Dijk.

6 recordsLinked to original sources

PubMed2006

Solvated docking: introducing water into the modelling of biomolecular complexes.

MOTIVATION: Interfacial water, which plays an important role in mediating biomolecular interactions, has been neglected in the modelling of biomolecular complexes. METHODS: We present a solvated docking approach that explicitly accounts for the presence of water in protein-protein complexes. Our solvated docking protocol is based on the concept of the first encounter complex in which a water layer is present in-between the molecules. It mimics the pathway from this initial complex towards the final assembly in which most waters have been expelled from the interface. Docking is performed from solvated biomolecules and waters are removed in a biased Monte Carlo procedure based on water-mediated contact propensities obtained from an analysis of high-resolution crystal structures. RESULTS: We demonstrate the feasibility of this approach for protein-protein complexes representing both 'wet' and 'dry' interfaces. Solvated docking leads to improvements both in quality and scoring. Water molecules are recovered that closely match the ones in the crystal structures. AVAILABILTY: Solvated docking will be made available in the future release of HADDOCK version 2.0 (http://www.nmr.chem.uu.nl/haddock).

Binding Sites↗

PubMed2006

Information-driven protein-DNA docking using HADDOCK: it is a matter of flexibility.

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.

Computational Biology↗

PubMed2006

WHISCY: what information does surface conservation yield? Application to data-driven docking.

Protein-protein interactions play a key role in biological processes. Identifying the interacting residues is a first step toward understanding these interactions at a structural level. In this study, the interface prediction program WHISCY is presented. It combines surface conservation and structural information to predict protein-protein interfaces. The accuracy of the predictions is more than three times higher than a random prediction. These predictions have been combined with another interface prediction program, ProMate [Neuvirth et al. J Mol Biol 2004;338:181-199], resulting in an even more accurate predictor. The usefulness of the predictions was tested using the data-driven docking program HADDOCK [Dominguez et al. J Am Chem Soc 2003;125:1731-1737] in an unbound docking experiment, with the goal of generating as many near-native structures as possible. Unrefined rigid body docking solutions within 10 A ligand RMSD from the true structure were generated for 22 out of 25 docked complexes. For 18 complexes, more than 100 of the 8000 generated models were correct. Our results demonstrates the potential of using interface predictions to drive protein-protein docking.

Binding Sites↗

PubMed2006

Combining NMR relaxation with chemical shift perturbation data to drive protein-protein docking.

The modeling of biomolecular complexes by computational docking using the known structures of their constituents is developing rapidly to become a powerful tool in structural biology. It is especially useful in combination with even limited experimental information describing the interface. Here we demonstrate for the first time the use of diffusion anisotropy in combination with chemical shift perturbation data to drive protein-protein docking. For validation purposes we make use of simulated diffusion anisotropy data. Inclusion of this information, which can be derived from NMR relaxation rates and reports on the orientation of the components of a complex with respect to the rotational diffusion tensor, substantially improves the docking results.

Anisotropy↗

PubMed2005

Various strategies of using residual dipolar couplings in NMR-driven protein docking: application to Lys48-linked di-ubiquitin and validation against 15N-relaxation data.

When classical, Nuclear Overhauser Effect (NOE)-based approaches fail, it is possible, given high-resolution structures of the free molecules, to model the structure of a complex in solution based solely on chemical shift perturbation (CSP) data in combination with orientational restraints from residual dipolar couplings (RDCs) when available. RDCs can be incorporated into the docking following various strategies: as direct restraints and/or as intermolecular intervector projection angle restraints (Meiler et al., J Biomol NMR 2000;16:245-252). The advantage of the latter for docking is that they directly define the relative orientation of the molecules. A combined protocol in which RDCs are first introduced as intervector projection angle restraints and at a later stage as direct restraints is shown here to give the best performance. This approach, implemented in our information-driven docking approach HADDOCK (Dominguez et al., J Am Chem Soc 2003;125:1731-1737), is used to determine the solution structure of the Lys48-linked di-ubiquitin, for which chemical shift mapping, RDCs, and (15)N-relaxation data have been previously obtained (Varadan et al., J Mol Biol 2002;324:637-647). The resulting structures, derived from CSP and RDC data, are cross-validated using (15)N-relaxation data. The solution structure differs from the crystal structure by a 20 degrees rotation of the two ubiquitin units relative to each other.

Algorithms↗

PubMed2005

Data-driven docking for the study of biomolecular complexes.

With the amount of genetic information available, a lot of attention has focused on systems biology, in particular 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 are not sufficient to gain structural insight into these. A wealth of biochemical and/or biophysical data can, however, readily 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. In this review we discuss and illustrate the various sources of data that can be used to map interactions and their combination with docking methods to generate structural models of the complexes. Finally a perspective on the future of this kind of approach is given.

Mass Spectrometry↗