Research within the computational structural biology group focuses on the development of reliable bioinformatics and computational approaches to predict, model and dissect biomolecular interactions at atomic level. For this, bioinformatics data, structural information and available biochemical or biophysical experimental data are combined to drive the modelling process. This is implemented and further developed in the widely used HADDOCK software for the modelling of biomolecular complexes (http://bonvinlab.org/software).

By following a holistic approach integrating various experimental information sources with computational structural biology methods we aim at obtaining a comprehensive description of the structural and dynamic landscape of complex biomolecular machines, adding the structural dimension to interaction networks and opening the route to systematic and genome-wide studies of biomolecular interactions.

Selected peer-reviewed publications

1.      E. Karaca, J.P.G.L.M. Rodrigues, A. Graziadei, A.M.J.J. Bonvin and T. Carlomagno. An Integrative Framework for Structure Determination of Molecular Machines. Nature Methods Advanced Online Publication (2017).

2.      G.C.P. van Zundert, M. Trellet, J. Schaarschmidt, Z. Kurkcuoglu, M. David, M. Verlato, A. Rosato and A.M.J.J. Bonvin. The DisVis and PowerFit web servers: Explorative and Integrative Modeling of Biomolecular Complexes. J. Mol. Biol., 429, 399-407 (2017).

3.      A Vangone and A.M.J.J. Bonvin. Contacts-based prediction of binding affinity in protein-protein complexes. eLife, 4, e07454 (2015).

4.      G.C.P. van Zundert, A.S.J. Melquiond and A.M.J.J. Bonvin(2015). Integrative modeling of biomolecular complexes: HADDOCKing with Cryo-EM data.Structure. 23, 949-960.

5.       P.L. Kastritis, J.P.G.L.M Rodrigues, G.E. Folkers, R. Boelens and A.M.J.J. Bonvin(2014). Proteins feel more than they see: Fine-tuning of binding affinity by properties of the non-interacting surface.?J. Mol. Biol.426, 2632-2652.

6.      E. Karaca and A.M.J.J. Bonvin(2011). A multi-domain flexible docking approach to deal with large conformational changes in the modeling of biomolecular complexes. Structure, 18,555-565.

7.      T. Schneider, Th. Kruse, R. Wimmer, I. Wiedemann, V. Sass, U. Pag, A. Jansen, A.K. Nielsen, P.H. Mygind, D.S. Raventós, S. Neve, B. Ravn, A.M.J.J. Bonvin, L. De Maria, L. Kamenova, H.-G. Sahl and H.-H. Kristensen (2010). Plectasin, a fungal defensin antibiotic peptide, targets the bacterial cell wall precursor Lipid II. Science,328, 1168-1172.

8.      P.L. Kastritis and A.M.J.J. Bonvin(2010). Are scoring functions in protein-protein docking ready to predict interactomes? Clues from a novel binding affinity benchmark. J. Proteome Res.,9, 2216-2225.

9.      S.J. de Vries, M. van Dijk and A.M.J.J. Bonvin(2010). The HADDOCK web server for data-driven biomolecular docking.Nature Protocols, 5, 883-897.

10.    C. Dominguez, R. Boelens and A.M.J.J. Bonvin(2003). HADDOCK: A protein-protein docking approach based on biochemical or biophysical information. J. Am. Chem. Soc.125, 1731-1737.