MCell4 with BioNetGen: A Monte Carlo simulator of rule-based reaction-diffusion systems with Python']Python interface

被引：2

作者：

Husar, Adam ^{[1
]}

Ordyan, Mariam ^{[2
]}

Garcia, Guadalupe C. ^{[1
]}

Yancey, Joel G. ^{[1
]}

Saglam, Ali S. ^{[3
]}

Faeder, James R. ^{[3
]}

Bartol, Thomas M. ^{[1
]}

Kennedy, Mary B. ^{[4
]}

Sejnowski, Terrence J. ^{[1
,2
]}

机构：

[1] Salk Inst Biol Studies, Computat Neurobiol Lab, La Jolla, CA 92037 USA

[2] Univ Calif San Diego, Inst Neural Computat, La Jolla, CA USA

[3] Univ Pittsburgh, Dept Computat & Syst Biol, Pittsburgh, PA USA

[4] CALTECH, Div Biol & Biol Engn, Pasadena, CA USA

来源：

PLOS COMPUTATIONAL BIOLOGY | 2024年 / 20卷 / 04期

关键词：

MODEL; SOFTWARE;

D O I：

10.1371/journal.pcbi.1011800

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Biochemical signaling pathways in living cells are often highly organized into spatially segregated volumes, membranes, scaffolds, subcellular compartments, and organelles comprising small numbers of interacting molecules. At this level of granularity stochastic behavior dominates, well-mixed continuum approximations based on concentrations break down and a particle-based approach is more accurate and more efficient. We describe and validate a new version of the open-source MCell simulation program (MCell4), which supports generalized 3D Monte Carlo modeling of diffusion and chemical reaction of discrete molecules and macromolecular complexes in solution, on surfaces representing membranes, and combinations thereof. The main improvements in MCell4 compared to the previous versions, MCell3 and MCell3-R, include a Python interface and native BioNetGen reaction language (BNGL) support. MCell4's Python interface opens up completely new possibilities for interfacing with external simulators to allow creation of sophisticated event-driven multiscale/multiphysics simulations. The native BNGL support, implemented through a new open-source library libBNG (also introduced in this paper), provides the capability to run a given BNGL model spatially resolved in MCell4 and, with appropriate simplifying assumptions, also in the BioNetGen simulation environment, greatly accelerating and simplifying model validation and comparison.

引用

页数：30