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Training module used during the 2019 International Incoherent Scatter Radar (ISR) School

Training material used during the "EMBO practical course on Practical Integrative Structural Biology" event

Training Material used during the NGSchool 2018

On this page, you can find the links to the HADDOCK and metadynamics (using Gromacs) tutorials given during the BioExcel Summer School on Biomolecular Simulations 2019 in Pula, Italy.

The first tutorial demonstrates the use of cross-linking data from mass spectrometry to guide protein-protein docking in HADDOCK.

The second tutorial illustrates how metadynamics can be used to sample conformations of a binding pocket; those are subsequently used for docking a ligand using HADDOCK. The conformational sampling approach is following the EDES approach described in the following publication:

• A. Basciu, G. Malloci, F. Pietrucci, A.M.J.J. Bonvin and A.V. Vargiu. Holo-like and druggable protein conformations from enhanced-sampling of binding pocket shape. J. Chem. Inf. and Mod. 59, 1515-1528 (2019).

DisVis is a software developed in our lab to visualise and quantify the information content of distance restraints between macromolecular complexes. It is open-source and available for download from our Github repository. To facilitate its use, we have developed a web portal for it.

This tutorial demonstrates the use of the DisVis web server. The server makes use of either local resources on our cluster, using the multi-core version of the software, or GPGPU-accelerated grid resources of the EGI to speed up the calculations. It only requires a web browser to work and benefits from the latest developments in the software based on a stable and tested workflow. Next to providing an automated workflow around DisVis, the web server also summarises the DisVis output highlighting relevant information and providing a first overview of the interaction space between the two molecules with images autogenerated in UCSF Chimera.

The case we will be investigating is the interaction between two proteins of the 26S proteasome of S. pombe, PRE5 (UniProtKB: O14250) and PUP2 (UniProtKB: Q9UT97). For this complex seven experimentally determined cross-links (4 ADH & 3 ZL) are available (Leitner et al., 2014). We added two false positive restraints - it is your task to try to identify these! For this, we use DisVis to try to filter out these false positive restraints while assessing the true interaction space between the two chains. We will then use the interaction analysis feature of DisVis that allows for a more complete analysis of the residues putatively involved in the interaction between the two molecules. To do so, we will extract all accessible residues of the two partners, and give the list of residues to DisVis using its interaction analysis feature. Finally, we will show how the restraints can be provided to HADDOCK in order to model the 3D interaction between the 2 partners.

This tutorial will demonstrate the use of HADDOCK for predicting the structure of a protein-protein complex from NMR chemical shift perturbation (CSP) data. Namely, we will dock two E. coli proteins involved in glucose transport: the glucose-specific enzyme IIA (E2A) and the histidine-containing phosphocarrier protein (HPr).

The structures in the free form have been determined using X-ray crystallography (E2A) (PDB ID 1F3G) and NMR spectroscopy (HPr) (PDB ID 1HDN). The structure of the native complex has also been determined with NMR (PDB ID 1GGR).

These NMR experiments have also provided us with an array of data on the interaction itself (chemical shift perturbations, intermolecular NOEs, residual dipolar couplings, and simulated diffusion anisotropy data), which will be useful for the docking. For this tutorial, we will only make use of inteface residues identified from NMR chemical shift perturbation data as described in Wang et al, EMBO J (2000).

This is a support guide for those who develop training materials and deliver training events using EOSC-hub efforts. The purpose is for WP11 to efficiently manage training delivery and improve the quality of these events. This document also intends to collect best practices from our experienced trainers -- this will help to share experiences within EOSC-hub and beyond.