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HADDOCK workshop on Information-driven modelling of biomolecular complexes
Provider: Faculty of Health and Medical Sciences

Activity no.: 3268-23-00-00 
Enrollment deadline: 07/10/2023
Date and time24.10.2023, at: 08:30 - 27.10.2023, at: 18:00
Regular seats30
Course fee1,800.00 kr.
LecturersGuillermo Montoya
ECTS credits3.50
Contact personLucy Holt    E-mail address: lucy.holt@bio.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: phdkursus@sund.ku.dk

Aim and content

This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member universities. All other participants must pay the course fee.

Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed on the waiting list until enrollment deadline. This also applies to PhD students from NorDoc member universities. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.

Learning objectives

A student who has met the objectives of the course will be able to:

• Students will obtain knowledge and hands on experience on basic principles of modelling biomolecular complexes (protein-protein and other types of complexes) and integrative modelling

• Students will have insight into how to integrate information derived from biochemical, biophysical or bioinformatics methods to enhance sampling, scoring, or both, using HADDOCK

• Students will be able to determine which data obtained from NMR spectroscopy, mutagenesis experiments, bioinformatics predictions and cryo-electron microscopy experiments that can be used for HADDOCK modeling and how they are incorporated

• Student will obtain competence in critical assessment of models obtained from HADDOCK

• Students will be able to model basic protein-docking, homo-oligomeric complexes from MS cross-links and shape-based small molecule docking using different dataset


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 flexible information-driven docking approach HADDOCK (http://www.bonvinlab.org/software). 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: among others interface restraints from NMR, mutagenesis experiments, or bioinformatics predictions and, recently, cryo-electron microscopy experiments.


This PhD course will be relevant for PhD students with a background in protein science, and the application of computational modelling to biological data.

The participants should have some basic structural biology knowledge and affinity with computing/computers. Some basis experience of Linux (command line) is expected.

Relevance to graduate programmes

The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

- Pharmaceutical Sciences (Drug Research Academy)
- Neuroscience
- Molecular Mechanisms of Disease




The course will consist of lectures and a hands-on session on computers during which participants will learn to use HADDOCK for the modelling for biomolecular complexes through its user-friendly web portal whose development and operations are supported by the BioExcel Center of Excellence for Computational Biomolecular Research and the EOSC-Hub H2020 projects.

The course will also include participation in two full-day meetings which are being planned in conjunction to the course and will follow directly after the teaching days. These meetings will explore leading scientific research in integrative structural biology and will include a talk by course teacher Alexandre Bonvin. They will also provide space where students can present their own research and course participants will be expected to contribute actively by presenting a poster.

Course director

Professor Guillermo Montoya, Center for Protein Research, guillermo.montoya@cpr.ku.dk


Professor Alexandre Bonvin, Utrecht University, the Netherlands.

Postdoc Marco Giulini, Utrecht University, the Netherlands.


24 - 27 October 2023

Course location



Please register before 7 October 2023

Expected frequency


Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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