Program

• Molecular dynamics overview

• Generative MD

• Boltzmann generators and emulators

• Implicit Transfer Operators

• The difficulty of evaluation

• Software practical on Implicit Transfer Operators

Monday late afternoon: 2-minute student presentations

Monday 7 PM: Dinner-buffet mixer at the IESC dining room

Part I: Simulation-based inference (R Covino)

• Introduction to Bayesian inference

• Neural estimators for Bayesian inference

Part II: Learning molecular conformational heterogeneity from cryo-electron microscopy and force spectroscopy (L Dingeldein) 

• Modelling single particle cryoEM experiments and using machine learning to assign conformations to single images

• Modelling single-molecule force spectroscopy experiments and extracting free energy surfaces

Part III: Learning mechanisms of plasma membrane proteins dimerisation dynamics from super resolution microscopy (M. Ramirez-Sierra)

• Modelling single-resolution experiments of plasma membrane proteins dynamics

• Learning protein dynamics directly from super resolution experimental videos

Wednesday 25th : Dynamic reweighting for unbinding processes

 Bettina Keller, Freie Universität Berlin, Germany

• Finding unbinding pathways with τ-RAMD

• Girsanov reweighting of biased simulations

• Neural-network approaches to learning the committor function from simulation data

ref: B.G. Keller, P.G. Bolhuis. "Dynamical reweighting for biased rare event simulations." Annual Review of Physical Chemistry 75.1 (2024): 137-162. https://doi.org/10.1146/annurev-physchem-083122-124538

• Hill's relation, splitting techniques for rare-event sampling

• Accelerated dynamics

Thursday 7 PM: Gala dinner at the IESC dining hall

Machine-learning based approaches for protein dynamics (F Cazals)

• Learning higher dimensional Ramachandran diagrams

• Sampling large amplitude conformational changes using kinematics and joint distributions of torsion angles

Modeling highly dynamic, intrinsically disordered proteins (J Cortés)

• Limitations of current deep-learning-based approaches.

• Combining sampling methods and experimental measurements to model disordered proteins and regions

Friday 3 PM: Bus departs for Ajaccio airport