Les Houches-TSRC Workshop on Protein Dynamics
Online workshop on May 18+19, 2021.
In-person meeting in Spring/Summer 2022 in the French Alps
This workshop is a forum for presenting, teaching and discussing results from the application of state-of-the-art experimental (including, but not limited to, optical spectroscopy, NMR spectroscopy, X-ray crystallography, XFELs, electron microscopy, AFM and scattering methods), and theoretical and computational approaches to studying protein dynamics.
The Les Houches – TSRC Protein Dynamics Workshop complements the long-standing TSRC Protein Dynamics Workshop, held every other year in the odd calendar years at the Telluride Science Research Center in Telluride, Colorado.
The workshop has been held on May 18+19, 2021.
Thanks to all our speakers, poster presenters and participants for great talks and discussions!
The plenary talks will be posted on the youtube channel of IST Austria, roughly around May 25.
Check it out here: https://www.youtube.com/user/ISTAustria
Online Workshop on May 18+19, 2021
Due to the special situation in 2020 and 2021, we have decided to bring the community together to exchange ideas and keep the spirit active. Thus, we are proud to have a great set of speakers for the 2021 online workshop.
Speakers: (click on title to see abstracts)
James Fraser: "Targeting COVID-19 Viral Enzymes in an Evolving Landscape of Publishing and Peer Review"
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) macrodomain within the nonstructural protein 3 counteracts host-mediated antiviral adenosine diphosphate-ribosylation signaling. This enzyme is a promising antiviral target because catalytic mutations render viruses nonpathogenic. We conducted a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Neutron diffraction data is guiding hydrogen placement to improve docking calculations. Several hits have promising activity in solution and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors. The role of entropy in modulating binding affinity will also be discussed.
Frank Noé: "Machine Learning for protein thermodynamics and kinetics"
Machine learning and high-performance simulation are helping us to make significant progress in all fields of science, and protein biophysics is no exception. In this talk, I will give an update of the state of the art in machine learning for protein biophysics and specifically focus on rare event sampling and detection, learning coarse-grained molecular dynamics force fields from all-atom simulations, and generating protein structures and thermodynamics via generative deep learning.
Dorothee Kern: "Time travel to the past and future – evolution of energy landscapes for enzymes catalysis"
Claus Seidel: "Integrative dynamic structural biology of proteins with multi-modal fluorescence spectroscopy "
Benoît Roux: "Using Computer Simulations to Advance our Understanding of Biological Systems at the Atomic Level"
Classical molecular dynamics (MD) simulations based on atomic models play an increasingly important role in a wide range of applications in physics, biology and chemistry. The approach consists of constructing detailed atomic models of the macromolecular system and, having described the microscopic forces with a potential function, using Newton's classical equation, F=MA, to literally "simulate" the dynamical motions of all the atoms as a function of time. The calculated trajectory, though an approximation to the real world, provides detailed information about the time course of the atomic motions, which is impossible to access experimentally. While great progress has been made, producing genuine knowledge about biological systems using MD simulations remains enormously challenging. Among the most difficult problems is the characterization of large conformational transitions occurring over long time scales. Issues of force field accuracy, the neglect of induced polarization in particular, are also a constant concern. A powerful paradigm for mapping the conformational landscape of biomolecular systems is to combine free energy methods, transition pathway techniques and stochastic Markov State Model based massively distributed simulations. These concepts will be illustrated with a few recent computational studies of Src tyrosine kinases, K+ channels, and the P-type ion pumps.
Information about our speakers:
"Poster-session" during online workshop.
Two poster sessions, one on May 18 and one on May 19, will allow us to see the latest results from ~30 participants. They will very briefly showcase their work in 90-second "flash" presentations, and then present their work in breakout rooms.
See the poster presenters and abstracts here
Registration (free of charge)
Enrica Bordignon (Ruhr University Bochum, Germany)
Matthias Heyden (Arizona State University, USA)
Paul Schanda (IBS, Grenoble, France / Institute of Science and Technology Austria)
Ben Schuler (University of Zurich, Switzerland)
Martin Weik (Institut de Biologie Structurale, Grenoble, France)
The Ecole de Physique des Houches is supported by: