ESDW6: Classical MD
- Peter Bolhuis (University of Amsterdam, The Netherlands)
- Christoph Dellago (University of Vienna, Austria)
- David Swenson (Universiteit van Amsterdam, The Netherlands)
During the past decades, classical molecular dynamics (MD) simulation has become a central tool in many branches of science and engineering. In particular, in molecular biology, chemistry and materials science, MD simulations now routinely provide insights into molecular mechanisms with a spatial and temporal resolution not accessible to experimental probes. While several software packages for MD simulations have been developed, opening the possibility to carry out such simulations to a broad community of researchers, the relatively short time scales accessible to MD simulations still limit the applicability of MD, particularly to processes dominated by rare but important barrier crossing events such as protein folding and binding, chemical reactions in solution and nucleation phenomena. The goal of WP1 is to create software modules that can be used in conjunction with existing programs to address the computational challenges caused by rare events. In particular, WP1 focuses on the development of user-friendly modules to sample rare barrier crossing trajectories and to analyze their molecular mechanisms.
First ESDW of WP1: The first Extended Software Development Workshop (ESDW1) of WP1 will take place from November 16-25, 2016, at the International Academy Traunkirchen (www.akademietraunkirchen.com) in Traunkirchen. During this workshop specific software modules for trajectory sampling and analysis will be developed.
Second ESDW of WP1: The second Extended Software Development Workshop (ESDW2) of WP1 will take place from August 14-25, 2017, at the CECAM-NL node in the Netherlands. The location will be the Lorentz Center, please consult the Lorentz page for the event here. ESDW2 is a follow-up on ESDW1 in which a second batch of modules will be developed, and previous modules will be expanded on. ESDW2 will focus on the creation of modules for rate calculations and enhanced path sampling.
Ten to twelve junior participants (mainly PhD students and postdocs) will take part in the workshop. The majority of these young scientists will have attended ESDW1. The workshop will start with introductory lectures on goals and topics of the workshop. Several senior researchers will give advanced background scientific lectures necessary for the topics, including a summary of the state-of the art science involved. This includes lectures on development guidelines and software engineering. The participants will then form work groups of 2-3 people and start work on specific software modules (see below). Each day of the workshop will be concluded by a documentation of the progress achieved.. The central goal of the workshop is to build new and extend existing software modules of WP1, firmly establish the involvement of the experience junior participants, and enable the novice junior participants to get involved in the project.
Software Modules for WP1: The main goal of WP1 is the creation of a library of python modules for path sampling and analysis. In particular, the following modules will be developed with the help of the participants of the so far two ESDWs:
• Basic shooting and shifting algorithm
• Biased path sampling
• Aimless shooting algorithm
• Reactive flux algorithm
• Calculation of the transition state ensemble
• Maximum likelihood optimization of the reaction coordinate
• Bootstrapping paths
• Rate constant calculation via transition interface sampling (TIS)
• Optimal placement of interfaces
• (Single) replica exchange TIS
• Sampling multiple state networks
• Multiple interface sets
• Reweighting schemes
• Interface with external order parameter module
• Analysis tools for path ensembles
• High performance and parallelization
The python modules interfaced with the OpenMM toolkit for high performance molecular simulations, which is available as open source code. OpenMM provides an efficient library of routines central for molecular simulation including the implementation of optimized forces fields, routines for building complex biomolecular and materials systems as well as molecular dynamics integrators for various statistical mechanical ensembles. What makes OpenMM particularly powerful as a molecular dynamics engine underlying the path sampling and analysis modules of WP1 is that it is extremely flexible and guarantees high performance through optimization on all common GPU platforms.
Python modules will be based upon functionality from NetCDF, numpy, and trajectories analysis tools such as MDTraj and Plumed. Modules will also directly interface with the OpenPathSampling framework.