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 modelling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process.
We have developed for this purpose a versatile information-driven docking approach HADDOCK (http://haddock.science.uu.nl ) . HADDOCK can integrate information derived from biochemical, biophysical or bioinformatics methods to enhance sampling, scoring, or both . The information that can be integrated is quite diverse with as most recent addition cryo-EM maps . In my talk, I will illustrate HADDOCK’s capabilities with various examples and describe some recent developments in the modelling of small molecules  to membrane protein complexes  and large assemblies.References
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2. J.P.G.L.M Rodrigues and A.M.J.J. Bonvin Integrative computational modeling of protein interactions. FEBS J., 281, 1988-2003 (2014).
3. G.C.P. van Zundert, A.S.J. Melquiond and A.M.J.J. Bonvin. Integrative modeling of biomolecular complexes: HADDOCKing with Cryo-EM data. Structure. 23, 949-960 (2015).
4. P.I. Koukos, L.C. Xue and A.M.J.J. Bonvin. Protein-ligand pose and affinity prediction. Lessons from D3R Grand Challenge 3. J. Comp. Aid. Mol. Des. 33, 83-91 (2019).
5. P.I. Koukos, I. Faro, C.W. van Noort and A.M.J.J. Bonvin. A membrane protein complex docking benchmark. J. Mol. Biol. 430, 5246-5256 (2018)