High-performance weighted ensemble software for simulation of complex bio-events

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High-performance weighted ensemble software for simulation of complex bio-events (Renewal) 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. The WESTPA software package is a powerful “meta tool” which can make possible computations which otherwise would be impossible within a given computing budget - while letting researchers continue to use simulation engines and models of their choice. WESTPA controls existing dynamics engines by orchestrating up to thousands of trajectories run natively by those packages at any scale (e.g., Gromacs, Amber, BioNetGen, MCell) using a “weighted ensemble” strategy. Not only does WESTPA automatically 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 and equilibrium observables in significantly less computing time than would be required in ordinary parallelization. The aims of the proposal are (i) to optimize WESTPA for cloud-computing, improving its ease of use, and developing highly scalable data storage analysis; (ii) to expand WESTPA’s base-computing power via algorithmic improvements; and (iii) to demonstrate the effectiveness of WESTPA through a series of “showcase” examples from molecular to cellular scale using a variety of dynamics engines. Completion of the aims will enable the investigators, their experimental and computational collaborators, and users throughout the world to make a wide range of contributions to the burgeoning field of biological simulation at multiple scales.