Developing A Bitwise Macromolecular Assembly Simulator

Abstract

Macromolecular machines play fundamental roles in many cellular tasks, from intracellular transport to protein synthesis and degradation. The majority of these machines must adopt a particular quaternary structure in order to function, and so understanding their assembly represents a critical component of our understanding of overall cellular physiology. Developing a theoretical and conceptual understanding of assembly has been hampered by the lack of general, efficient and scalable computational tools for simulating assembly processes. In this work, we develop a new framework that employs a bitwise representation of assembly intermediates. Using this framework, we have implemented a Bitwise Macromolecular Assembly Simulator (BMAS). This software leverages our binary representation of intermediates to perform most crucial computational steps using bitwise operators. This allows us to perform highly efficient Gillespie-style stochastic simulations of macromolecular assembly, resulting in a general simulation approach that is orders of magnitude faster than existing methods. Our approach is efficient enough to study of a wide variety of macromolecular machines, in addition to providing a tool that should assist in the design of novel self-assembling nanomaterials.