Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics.

@article{Vijaykumar2017MultiscaleSO,
  title={Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics.},
  author={Adithya Vijaykumar and Thomas E. Ouldridge and Pieter Rein ten Wolde and Peter G. Bolhuis},
  journal={The Journal of chemical physics},
  year={2017},
  volume={146 11},
  pages={
          114106
        }
}
The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we… 

Multi-scale simulation of reaction-diffusion systems

In many reaction-diffusion processes, ranging from biochemical networks, catalysis, to complex self-assembly, the spatial distribution of the reactants and the stochastic character of their

An efficient multi-scale Green's function reaction dynamics scheme.

It is shown that the choice of the propagation domains has a relevant impact on the computational performance and the algorithm is shown to be more efficient than brute-force Brownian dynamics simulations up to a molar concentration of 103 μM and is up to an order of magnitude more efficient compared with previous MD-GFRD schemes.

Modeling the Self-Assembly of Protein Complexes through a Rigid-Body Rotational Reaction-Diffusion Algorithm.

This work develops a relatively simple but accurate approach for building rigid structure and rotation into single-particle reaction-diffusion methods, providing a rate-based method for studying protein self-assembly and demonstrates how formation of regular lattices impacts the kinetics of association.

Multiscale molecular kinetics by coupling Markov state models and reaction-diffusion dynamics.

This paper presents a meta-modelling system that automates the very labor-intensive and therefore time-heavy and expensive and therefore expensive and expensive process of inferring Boltzmann's inequality in theorems.

MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations.

The first step toward MSM/RD is made by laying out a general theory of coupling and proposing a first implementation for association/dissociation of a protein with a small ligand and applications on a toy model and CO diffusion into the heme cavity of myoglobin are reported.

Grand canonical diffusion-influenced reactions: A stochastic theory with applications to multiscale reaction-diffusion simulations.

The grand canonical Smoluchowski master equation (GC-SME) is introduced, which consists of a continuous-time Markov chain that models an arbitrary number of B particles, each one of them following Smoluchi's probabilistic dynamics, and is exploited to accurately derive multiscale/hybrid numerical methods that couple particle-based reaction-diffusion simulations with bulk concentration descriptions.

ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics

The iPRD software ReaDDy 2 is introduced, 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.

Reversible Interacting-Particle Reaction Dynamics.

It is shown that in dense particle systems, the incorporation of detailed balance is essential to obtain physically realistic solutions and a Monte Carlo algorithm is introduced that ensures detailed balance in the iPRD time-evolution (iPRD-DB).

An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology

An algorithm for reversible binding of proteins to continuum surfaces with implicit lipids, providing dramatic speed-ups to many body simulations, and will enable efficient cell-scale simulations involving proteins localizing to realistic membrane models, which is a critical step for predictive modeling and quantification of in vitro and in vivo dynamics.

Impact of Solution Chemistry and Particle Anisotropy on the Collective Dynamics of Oriented Aggregation.

Using Monte Carlo simulations, it is found that a simple geometric parameter, namely, the contact area between two attaching nanoplatelets, presents a useful tool for correlating nanoparticle morphologies to the emerging larger-scale aggregates, hence explaining the unusually high fractal dimensions measured for boehmite aggregates.

References

SHOWING 1-10 OF 58 REFERENCES

Combining molecular dynamics with mesoscopic Green's function reaction dynamics simulations.

A novel approach is proposed that combines GFRD for simulating the system at the mesoscopic scale where particles are far apart, with a microscopic technique such as Langevin dynamics or Molecular Dynamics, forSimulating theSystem at the microscopic scale where reactants are in close proximity.

Green's-function reaction dynamics: a particle-based approach for simulating biochemical networks in time and space.

We have developed a new numerical technique, called Green's-function reaction dynamics (GFRD), that makes it possible to simulate biochemical networks at the particle level and in both time and

Simulating biochemical networks at the particle level and in time and space: Green's function reaction dynamics.

We present a technique, called Green's function reaction dynamics (GFRD), for particle-based simulations of reaction-diffusion systems. GFRD uses a maximum time step such that only single particles

ReaDDy - A Software for Particle-Based Reaction-Diffusion Dynamics in Crowded Cellular Environments

The software package ReaDDy is introduced for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution, and has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics.

Free-Propagator Reweighting Integrator for Single-Particle Dynamics in Reaction-Diffusion Models of Heterogeneous Protein-Protein Interaction Systems

Free-propagator reweighting (FPR) applications include the modeling of pathways and networks of protein-driven processes where reaction rates can vary widely and thousands of proteins may participate in the formation of large assemblies, and can account for changes to reaction rates or diffusion constants as a result of reaction events.

The two-regime method for optimizing stochastic reaction–diffusion simulations

The two-regime method (TRM) is developed, in which a molecular-based algorithm is used where desired and a compartment-based approach is used elsewhere, and the TRM combines strengths of previously developed stochastic reaction–diffusion software to efficiently explore the behaviour of biological models.

Rotational diffusion affects the dynamical self-assembly pathways of patchy particles

The kinetic network of simple models for proteins and patchy colloids is studied and it is found that their dynamical self-assembly pathways change with varying the rotational diffusion constant, which enhances the overall relaxation process and the yield of the target structure, by avoiding (encountering) frustrated states.

Stochastic simulation of chemical reactions with spatial resolution and single molecule detail

Methods are presented for simulating chemical reaction networks with a spatial resolution that is accurate to nearly the size scale of individual molecules. Using an intuitive picture of chemical

Analysis of Brownian Dynamics Simulations of Reversible Bimolecular Reactions

A class of Brownian dynamics algorithms for stochastic reaction-diffusion models which include reversible bimolecular reactions is presented and analyzed and the probability of geminate recombination is investigated.

The Macroscopic Effects of Microscopic Heterogeneity in Cell Signaling

This chapter reviews examples of both explicitly imposed and intrinsic correlations, focusing on the mechanisms by which microscopic heterogeneity is amplified to macroscopic effect.
...