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 reactiondiffusion 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.
Currently, a significant barrier to building predictive models of cell-based self-assembly processes is that molecular models cannot capture minutes-long cellular dynamics that couple distinct components with active processes, while reaction-diffusion models lack sufficient detail for capturing assembly structures. Here we introduce the Non-Equilibrium Reaction-Diffusion Selfassembly Simulator (NERDSS), which addresses this gap by integrating a structure-resolved reaction-diffusion algorithm with rule-based model construction. By representing proteins as rigid, multi-site molecules that adopt well-defined orientations upon binding, NERDSS simulates formation of large reversible structures with sites that can be acted on by reaction rules. We show how NERDSS allows for directly comparing and optimizing models of multi-component assembly against time-dependent experimental data. Applying NERDSS to assembly steps in clathrin-mediated endocytosis, we capture how the formation of clathrin caged structures can be driven by modulating the strength of clathrin-clathrin interactions, by adding cooperativity, or by localizing clathrin to the membrane. NERDSS further predicts how clathrin lattice disassembly can be driven by enzymes that irreversibly change lipid populations on the membrane. By modeling viral lattice assembly and recapitulating oscillations in protein expression levels for a circadian clock model, we illustrate the wide usability and 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.
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