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Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

Lattice Microbes: high-performance stochastic simulation method for the reaction-diffusion master equation.

Elijah Roberts¹, John E Stone, Zaida Luthey-Schulten

¹Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.

Journal of Computational Chemistry

|September 26, 2012

Summary

This summary is machine-generated.

Lattice Microbes is new open-source software for spatial stochastic simulations of cellular processes on high-performance computing systems. It enables fast and accurate modeling of reactions, integrating diverse biological data for comprehensive cell simulations.

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Area of Science:

Computational Biology
Biophysics
Biochemistry

Background:

Spatial stochastic simulation is crucial for understanding biological reactions.
High-performance computing (HPC) enables complex cellular modeling.
Integrating diverse biological data into computational models is a key challenge.

Purpose of the Study:

Introduce Lattice Microbes, a software package for simulating cell models on HPC systems.
Enable fast and efficient spatial stochastic simulations with approximated cytoplasmic crowding.
Facilitate the integration of structural, single-molecule, and biochemical data into cell models.

Main Methods:

Developed a novel algorithm for efficient sampling of the reaction-diffusion master equation.
Utilized NVIDIA graphics processing units (GPUs) for accelerated simulations.
Integrated with the VMD visualization platform for model display and trajectory animation.

Main Results:

Lattice Microbes performs well-stirred and spatially resolved stochastic simulations.
The new algorithm achieves speeds two orders of magnitude faster than exact sampling for large systems.
Maintained high accuracy of !0.1% in simulations.
Facilitates visualization of reaction trajectories involving millions of molecules.

Conclusions:

Lattice Microbes provides a fast, efficient, and accurate platform for spatial stochastic simulations of cellular systems on HPC.
The software facilitates the creation of comprehensive computational cell models by integrating diverse biological data.
Open-source availability promotes wider adoption and advancement in computational biology.