Atomistic Monte Carlo Simulations of Bio-molecular Systems
Computer simulations have long been used to provide a conceptual framework to understand biophysical phenomena. Because of the high degree of complexity arising from the large number of interacting components, they constitute an essential class of tools in interpreting experimental studies, connecting them to fundamental physics, organizing our knowledge and asking new questions based on an ever improving picture.
A physics based picture of biomolecular processes allows us to make sense of, for instance, folding and interaction of proteins with their environment under different physical conditions, behaviour of intrinsically disordered proteins, and supra-molecular assembly processes such as peptide aggregation and coacervation. Such processes typically involve thousands of interacting entities, complex interactions and inconveniently long time scales. Typically researchers use multiple theoretical and experimental sources of information to circumvent the limitations of any single tool and extract useful insights despite those limitations.
The main objective of this tutorial is to introduce researchers to the principal characteristics and capabilities of atomistic Monte Carlo simulations.
In particular the tutorial will highlight commonalities and differences of atomistic MC to molecular dynamics simulations and discuss both their advantages and limitations to allow the attendants to judge where MC simulations may be helpful in their research and where not.
The tutorial comprises an introductory afternoon providing the necessary theoretical background followed by three days of hands-on sessions, where the participants will be given short expositions on a variety of Monte Carlo techniques followed by illustrative computer exercises. The topics will range from an elementary introduction to Markov Chain Monte Carlo simulations, through generalized ensemble techniques like replica exchange, to more advanced use cases, involving additional available information (noisy experimental data, uncertain predictions obtained using other theoretical methods, etc. ) about the simulated system. The tutorial will conclude with a discussion on current challenges and future development of MCMC methods. A kind of SWOT analysis (strengths, weaknesses, opportunities, threats) is meant to provide a critical analysis of the technique, discuss common pitfalls and potential extensions.
The three days of practical sessions will allow attendants to harness all capabilities of modern MC simulation techniques. During the tutorial, the participants will have access to HPC clusters of the Jülich Supercomputing Centre to run increasingly sophisticated simulations and perform in-depth analysis.
Jan Meinke (Forschungszentrum Juelich) - Organiser
Sandipan Mohanty (Forschungszentrum Jülich) - Organiser
Olav Zimmermann (Forschungszentrum Juelich) - Organiser