NERDSS: A Nonequilibrium Simulator for Multibody Self-Assembly at the Cellular Scale
Overview
Affiliations
Currently, a significant barrier to building predictive models of cellular self-assembly processes is that molecular models cannot capture minutes-long dynamics that couple distinct components with active processes, whereas reaction-diffusion models cannot capture structures of molecular assembly. Here, we introduce the nonequilibrium reaction-diffusion self-assembly simulator (NERDSS), which addresses this spatiotemporal resolution gap. NERDSS integrates efficient reaction-diffusion algorithms into generalized software that operates on user-defined molecules through diffusion, binding and orientation, unbinding, chemical transformations, and spatial localization. By connecting the fast processes of binding with the slow timescales of large-scale assembly, NERDSS integrates molecular resolution with reversible formation of ordered, multisubunit complexes. NERDSS encodes models using rule-based formatting languages to facilitate model portability, usability, and reproducibility. Applying NERDSS to steps in clathrin-mediated endocytosis, we design multicomponent systems that can form lattices in solution or on the membrane, and we predict how stochastic but localized dephosphorylation of membrane lipids can drive lattice disassembly. The NERDSS simulations reveal the spatial constraints on lattice growth and the role of membrane localization and cooperativity in nucleating assembly. By modeling viral lattice assembly and recapitulating oscillations in protein expression levels for a circadian clock model, we illustrate the adaptability of NERDSS. NERDSS simulates user-defined assembly models that were previously inaccessible to existing software tools, with broad applications to predicting self-assembly in vivo and designing high-yield assemblies in vitro.
Mechanisms of enhanced or impaired DNA target selectivity driven by protein dimerization.
Sang M, Johnson M bioRxiv. 2025; .
PMID: 40027831 PMC: 11870488. DOI: 10.1101/2025.02.18.638941.
Predicting protein curvature sensing across membrane compositions with a bilayer continuum model.
Fu Y, Johnson D, Beaven A, Sodt A, Zeno W, Johnson M bioRxiv. 2025; .
PMID: 39763813 PMC: 11702529. DOI: 10.1101/2024.01.15.575755.
Parallelization of particle-based reaction-diffusion simulations using MPI.
Guo S, Korolija N, Milfeld K, Jhaveri A, Sang M, Ying Y bioRxiv. 2024; .
PMID: 39713431 PMC: 11661114. DOI: 10.1101/2024.12.06.627287.
Qiao L, Getz M, Gross B, Tenner B, Zhang J, Rangamani P PLoS Comput Biol. 2024; 20(10):e1012564.
PMID: 39480900 PMC: 11556706. DOI: 10.1371/journal.pcbi.1012564.
Vesiculation pathways in clathrin-mediated endocytosis.
Wang X, Berro J, Ma R bioRxiv. 2024; .
PMID: 39185216 PMC: 11343097. DOI: 10.1101/2024.08.13.607731.