Lectures are from 9 AM to noon, Practicals from 2 to ~5 PM. (Exact times may vary)

Links to lecture notes and practicals info will be added to each day as needed.

Monday, 21 Nov: Introduction and overview of IDPs

Peter Tompa, Vrije Universiteit Brussels, Belgium

Sonia Longhi, CNRS AFMB & Aix-Marseille Université, Marseille, France

Nathalie Sibille, CNRS Centre de Biochimie Structurale de Montpellier, France

Image of p53 protein bound to DNA

Morning: a general introduction to intrinsically disordered proteins through a historical perspective to the most recent developments.

  • brief history and basic concepts
  • biophysical methods for the characterization of structural disorder
  • functions and functional classification of disordered proteins
  • structural disorder in diseases: can we target IDPs?
  • ...

Afternoon: recent progress in database development

Monday, 21 Nov, after the practical: Participants Session

Short presentations (≤ 3 min) to tell about your research interests

Please prepare a single slide (pdf format) ready to project.

This session will be followed by an apéro with a mini-buffet so we can all meet each other

Tuesday, 22 Nov: Sampling the conformational space, structural, thermodynamic and kinetic modelling

Gerhard Hummer, Max Planck Institute for Biophysics, Frankfurt am Main, Germany

The practical session will be assisted by Johannes Betz, Henry Kim, and Maziar Haidari: Installation info

[Pietrek, Stelzl, & Hummer, J. Chem. Theory Comput. 2020]

Description of the practical session

  1. Hierarchical Chain Growth
    • Working with complete code of a functional HCG implementation for a simplified case
  2. Bayesian Ensemble Refinement
    • Reweighting the HGC ensemble according to SAXS data via Bayesian Inference of Enesembles (BioEn)
  3. Coarse-Grained Simulation
    • Homopolymer model calculations
    • MARTINI simulation of an IDP
  4. Comparison of Experimental Observables between Models

Wednesday, 23 Nov: Connecting conformational ensembles to experimental results

Martin Blackledge, Institut de Biologie Structurale, Grenoble, France

Practical session info is available at: Practical course info

  • Statistical coil sampling of unfolded states
  • Simulation of measurables and comparison with experimental values. Importance of averaging. This will include PREs, CSs, SAXS, RDCs.
  • Simulation of NMR relaxation - importance of correct treatment of angular correlation functions/sampling of the conformational ensemble.
  • Interactions between IDPs and partners - exchange methods and how these can be used to enhance our understanding of disorder in biology.
  • Examples of the above, and biological insight that can be derived

Thursday, 24 Nov: Modelling phase separation in the cell

Jeetain Mittal, Chemical Engineering Department, Texas A&M University, College Station, Texas, USA

Jeetain Mittal's practical session installation info

The morning lecture and the afternoon practical will cover physics-based computational models that we have been developing in close collaboration with experimental collaborators for the last ten years.

The lecture will provide a broad overview of available atomistic and coarse-grained models and their relative benefits for specific research problems. A particular emphasis will be a discussion of models suitable for studying the liquid-liquid phase separation of proteins and nucleic acids.

The practical will cover the software and scripts necessary to use our coarse-grained modeling framework capable of providing molecular-level details on the sequence-determinants of protein phase separation due to specific disease mutations and the inclusion of a folded domain, and variation of chain length.

Thursday, 24 Nov: "Gala" Dinner at the IESC

Friday, 25 Nov: Novel algorithms for exploring and characterizing high-dimensional conformational spaces

Juan Cortés, CNRS LAAS, Toulouse, France

Frédéric Cazals, Inria, Sophia-Antipolis

A (short) practical session will be held, assisted by Javier Gonzalez-Delgado: Installation info

Robot path-planning for IDP conformations Simplifying a complex PEL

Part I:

  • Modeling proteins in internal coordinates: a robotics-inspired approach
  • Tripeptides as basic elements to model highly-flexible proteins and regions
  • Structural propensity prediction from IDP sequences based on a structural database of tripeptides
  • Generation of conformational ensemble models of IDPs/IDRs

Part II:

  • Distance based structural measures: least RMSD and combined RMSD
  • Nearest neighbor graphs of conformations and energy landscape models
  • Persistence based analysis of energy landscapes
  • Applications to IDPs


  1. Predicting secondary structure propensities in IDPs using simple statistics from three-residue fragments; A. Estaña, A. Barozet, A. Mouhand, M. Vaisset, C. Zanon, P. Fauret, N. Sibille, P. Bernadó, J. Cortés; Submitted.
  2. Realistic ensemble models of intrinsically disordered proteins using a structure-encoding coil database; A. Estaña, N. Sibille, E. Delaforge, M. Vaisset, J. Cortés, P. Bernadó; Structure, 27(5): 381-391.e2, 2019
  3. A reinforcement-learning-based approach to enhance exhaustive protein loop sampling; A. Barozet, K. Molloy, M. Vaisset, T. Siméon, J. Cortés; Bioinformatics, 36(4): 1099-1106, 2020
  4. Characterizing molecular flexibility by combining lRMSD measures; F. Cazals, and R. Tetley; Proteins, 87 (5), 2019.
  5. Energy landscapes and persistent minima; J. Carr, and D. Mazauric, and F. Cazals, and D. Wales; The Journal of Chemical Physics, 144 (5), 2016
  6. Conformational Ensembles and Sampled Energy Landscapes: Analysis and Comparison; F. Cazals, and T. Dreyfus, and D. Mazauric, and A. Roth, and C.H. Robert; J. Comp. Chem., 36 (16), 2015.

Friday afternoon: Bus back to the Ajaccio airport following the practical session.