Abstract

Interacting-particle reaction dynamics (iPRD) combines the simulation of dynamical trajectories of interacting particles as in molecular dynamics (MD) simulations with reaction kinetics, in which particles appear, disappear, or change their type and interactions based on a set of reaction rules. This combination facilitates the simulation of reaction kinetics in crowded environments, involving complex molecular geometries such as polymers, and employing complex reaction mechanisms such as breaking and fusion of polymers. iPRD simulations are ideal to simulate the detailed spatiotemporal reaction mechanism in complex and dense environments, such as in signalling processes at cellular membranes, or in nano- to microscale chemical reactors. Here we introduce the iPRD software ReaDDy 2, which provides a Python interface in which the simulation environment, particle interactions and reaction rules can be conveniently defined and the simulation can be run, stored and analyzed. A C++ interface is available to enable deeper and more flexible interactions with the framework. The main computational work of ReaDDy 2 is done in hardware-specific simulation kernels. While the version introduced here provides single- and multi-threading CPU kernels, the architecture is ready to implement GPU and multi-node kernels. We demonstrate the efficiency and validity of ReaDDy 2 using several benchmark examples. ReaDDy 2 is available at the https://readdy.github.io/ website.

Highlights

  • The physiological response of biological cells to stimuli can be a many-stage process

  • Several aspects of the model applied in ReaDDy 2 are validated and demonstrated by considering different application scenarios and comparing the results to analytically obtained results, simulations from other packages, or literature data

  • Results of the ReaDDy 2 framework are compared to other simulation frameworks and analytical results for validation

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Summary

Introduction

The physiological response of biological cells to stimuli can be a many-stage process. A widely studied example is the MAPK pathway [1, 2] Many of such signaling pathways incorporate Gprotein coupled receptors (GPCR) [3] and cyclic adenosine monophosphate (cAMP) [4]. These are related to various diseases [5,6,7]. An extracellular stimulus can activate the membrane bound GPCRs and lead to localized synthesis of cAMP as second messengers. Their transport through the cell is diffusive, due to the geometry of cellular compartments cAMP molecules are non-uniformly distributed [8, 9]. Their presence needs to be resolved in space and time to understand their function

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