SGER: Discrete Event Simulation of Self-Assembly Kinetics

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

EIA-0320595 Russell Schwartz Carnegie Mellon University Project Summary: Discrete Event Simulation of Self-Assembly Kinetics The goal of this project is to develop a novel computational tool for simulating generalized self- assembly systems. Self-assembly systems consist of many small components, or subunits, that spontaneously arrange themselves into larger structures under appropriate conditions. Among the many medically important self-assembly systems are viral protein shells, or capsids, which form protective coats around the genetic material of viruses; amyloids, fibrous agglomerations of proteins that are implicated in Alzheimer.s disease, Huntington.s disease, and the prion diseases; and irregular protein aggregates. For all of these systems, the process of assembly is only partially understood. In addition, self-assembly has attracted recent interest as a means of constructing man-made devices and materials on the nanometer scale. Due to the small size, speed, and complexity of many self-assembly processes, they have proven difficulty to analyze experimentally. Simulation approaches have therefore emerged as a crucial avenue for gaining insight into the self-assembly process. This project seeks to build on the prior work in the area by creating a model of the self-assembly process sufficiently versatile to capture a wide variety of self-assembly systems, yet fast enough to handle realistic simulation sizes in a reasonable time. The basic methodology will involve combining techniques developed in prior modeling work on this problem with a computational method that has not previously been used for self-assembly simulation. The simulator will use a model of self-assembly dynamics based largely on the prior .local rules dynamics. model, which provided a versatile representation of high-level self- assembly behavior in terms of low-level subunit interactions. It will be efficiently implemented using a computational data structure called a .discrete event priority queue,. which will allow the simulator to step between changes in discrete state (such as subunits binding to one another) without the need for explicit integration over all time steps. The result will be faster simulation of a highly general self-assembly model than was possible with prior methods. The simulator will be implemented in Java to facilitate ease of development, extensibility, and portability. Implementation will be conducted through distinct phases devoted to developing an object model (which specifies how pieces of computer code interact with one another), coding and testing a prototype simulator, and finalizing an optimized and well documented release-quality version. The end result will be both a stand-alone simulation tool and a set of computational classes available for extension and use in other programs. This work will require innovation primarily in mathematical models of self-assembly processes and in algorithms for their efficient simulation by a discrete event queue methodology. Further innovation will be needed in the integration of existing knowledge from such areas as biophysics, algorithms, software engineering, and user interface design to produce a versatile, easy-to-use graphical simulation tool. The project can be expected to yield several benefits. Its impact will be primarily on the field of self-assembly, by providing a general tool that can be used by researchers throughout the field for modeling known systems across size and time scales, developing computational prototypes of novel systems, and experimenting with interventions in both. It will also provide new methods and experience to the general field of biophysical simulation through the development of a novel simulation methodology, its implementation in a computational simulator, and optimization of algorithms for this problem. The cross-disciplinary nature of the project will enhance its impact by providing for the computational community new variations on problems to be found in biophysical systems and providing for the biophysics community new computational techniques that can be brought to bear on other problems. The work will also have educational value by providing interdisciplinary research experience to students, including two undergraduates, and by providing a simulator that can be used as both a research and a teaching tool.