BioExcel CoE is launching new series of educational webinars for computational biomolecular research. The series will cover broad topics related to the latest development of major software packages; their application to modelling and simulation; best practices for performance tuning and efficient usage on HPC and novel architectures; introductory tutorials for novel users and much more.

The webinars include an audience Q&A session during which attendees can ask questions and make suggestions. They are a great opportunity to interact with the main code developers.

Our first webinar in the series will be:

Webinar: “Integrative modelling of biomolecular complexes with HADDOCK”
Presenter: Alexandre Bonvin
Date: Friday,  Apr 29, 2016
Time: 16:00-17:00 CET (Central European Time)

Registration: Free – register online at https://attendee.gotowebinar.com/register/7197777060128771 . After registering, you will receive a confirmation email containing information about joining the webinar.

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Integrative modelling of biomolecular complexes with HADDOCK.

Alexandre M.J.J. Bonvin

Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands.

a.m.j.j.bonvin@uu.nl

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://www.bonvinlab.org/software/haddock2.2) [1-3]. HADDOCK can integrate information derived from biochemical, biophysical or bioinformatics methods to enhance sampling, scoring, or both [4]. The information that can be integrated is quite diverse: interface restraints from NMR, mutagenesis experiments, or bioinformatics predictions; shape data from small-angle X-ray scattering [5] and, recently, cryo-electron microscopy experiments [6].

References

  1.     G.C.P van Zundert, J.P.G.L.M. Rodrigues, M. Trellet, C. Schmitz, P.L. Kastritis, E. Karaca, A.S.J. Melquiond, M. van Dijk, S.J. de Vries and A.M.J.J. Bonvin. The HADDOCK2.2 webserver: User-friendly integrative modeling of biomolecular complexes. J. Mol. Biol., 428, 720-725 (2015).
  2.     S.J. de Vries, M. van Dijk and A.M.J.J. Bonvin The HADDOCK web server for data-driven biomolecular docking. Nature Protocols, 5, 883-897 (2010).
  3.     C. Dominguez, R. Boelens and A.M.J.J. Bonvin HADDOCK: A protein-protein docking approach based on biochemical or biophysical information. J. Am. Chem. Soc., 125, 1731-1737 (2003).
  4.     J.P.G.L.M Rodrigues and A.M.J.J. Bonvin Integrative computational modeling of protein interactions. FEBS J., 281, 1988-2003 (2014).
  5.     E. Karaca and A.M.J.J. Bonvin. On the usefulness of Ion Mobility Mass Spectrometry and SAXS data in scoring docking decoys. Acta Cryst. D., D69, 683-694 (2013).
  6.     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).”