There is a silicon ceiling that ultimately limits many, if not most, types of dynamical biological simulations. That is, even the world's most powerful computers cannot generate sufficiently long simulations, whether for atomistic models of proteins or for realistic models of cell behavior. In many cases, the key events may occur beyond simulation timescales - such as protein folding, conformational transitions of proteins, assembly of protein complexes, or transitions of cell behavior from healthy to pathological states. We therefore propose a response to PA-14-156, Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics and Big Data Science (RO1), in which we will continue to enhance the WESTPA software package. WESTPA is a tool for controlling other software tools: it orchestrates up to thousands of trajectories run natively by other software at any scale (e.g., Gromacs, Amber, BioNetGen, MCell) using a weighted ensemble strategy. Not only does WESTPA parallelize the use of dynamics engines - but because of the statistical process by which trajectories are added and removed, WESTPA can obtain estimates of key kinetic as well as equilibrium observables in significantly less computing time than would be required in ordinary parallelization.
The aims of the proposal are to improve the ease of use and interoperability of WESTPA; to improve its performance and reliability; to demonstrate the effectiveness of WESTPA through a series of showcase examples from molecular to cellular scale using a variety of dynamics engines; and to improve instructional materials based on the showcase examples.
In response to a call from NIH, the aims to provide open-source software to enhance the power of simulations at any scale (e.g. molecular, cellular) for a potentially large user base. Thus, the primary impact will be to facilitate key segments of the burgeoning field of computational biomedical research. Additionally, research to be performed directly by the investigators is designed to yield insights into cancer and neurological processes with potential to enhance drug design efforts.
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