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

Hoffmann, Moritz; Fröhner, Christoph; Noé, Frank

doi:10.1371/journal.pcbi.1006830

Cited by 69 publications

(67 citation statements)

References 79 publications

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“…Our work attempts to bridge this gap, connecting sub-molecular states with the kinetics that provide inputs for models of the signaling cascade. While the coarse granularity omits many details, such as sequence-dependent persistence lengths (62), we join a growing body of modeling efforts (63,64) at the granularity between particles representing individual proteins and particles representing individual atoms, which has been particularly fruitful for intrinsically disordered domains (10-12, 22, 65) Multi-site reactions can be classified in two categories: sequential or random. For CD3ζ, evidence for sequential phosphorylation is mixed (54,66,67).…”

Section: Discussionmentioning

confidence: 99%

Intrinsic disorder in the T cell receptor creates cooperativity and controls ZAP70 binding

Clemens

Dushek

Allard³

2020

Preprint

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Many immunoreceptors have cytoplasmic domains that are intrinsically disordered (i.e., have high configurational entropy), have multiple sites of post-translational modification (e.g., tyrosine phosphorylation), and participate in nonlinear signaling pathways (e.g., exhibiting switch-like behavior). Several hypotheses to explain the origin of these nonlinearities fall under the broad hypothesis that modification at one site changes the immunoreceptor's entropy, which in turn changes further modification dynamics. Here we use coarse-grain simulation to study three scenarios, all related to the chains that comprise the T Cell Receptor. We find that, first, if phosphorylation induces local changes in the flexibility of the TCR ζ-chain, this naturally leads to rate enhancements and cooperativity. Second, we find that TCR CD3 can provide a switch by modulating its residence in the plasma membrane. By constraining our model to be consistent with the previous observation that both basic residues and phosphorylation control membrane residence, we find that there is only a moderate rate enhancement of 10% between first and subsequent phosphorylation events. And third, we find that volume constraints do not limit the number of ZAP70s that can bind the TCR, but that entropic penalties lead to a 200-fold decrease in binding rate by the seventh ZAP70, potentially explaining the observation that each TCR has around six ZAP70 molecules bound following receptor triggering. In all three scenarios, our results demonstrate that phenomena that change an immunoreceptor chain's entropy (stiffening, confinement to a membrane, and multiple simultaneous binding) can lead to nonlinearities (rate enhancement, switching, and negative cooperativity) in how the receptor participates in signaling. These polymer-entropy-driven nonlinearities may augment the nonlinearities that arise from, e.g., kinetic proofreading and cluster formation. They also suggest different design strategies for engineered receptors, e.g., whether or not to put signaling modules on one chain or multiple clustered chains. STATEMENT OF SIGNIFICANCEMany of the proteins involved in signal processing are both mechanically flexible and have multiple sites of interaction, leading to a combinatorial complexity making them challenging to study. One example is the T Cell Receptor, a key player in immunological decision making. It consists of 6 flexible chains with 20 interaction sites, and exhibits nonlinear responses to signal inputs, although the mechanisms are elusive. By using polymer physics to simulate the T Cell Receptor's chains, this work demonstrates that several of the nonlinear responses observed experimentally emerge naturally due to constraints on the chains that change their entropy. This work points to new avenues to modulate signaling proteins for therapeutics by modulating their mechanical flexibility and spatial extent.Challenging the tenet that "structure determines function", more than 40% of human proteins contain intrinsically disordered regions longer than...

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Section: Discussionmentioning

confidence: 99%

Intrinsic disorder in the T cell receptor creates cooperativity and controls ZAP70 binding

Clemens

Dushek

Allard³

2020

Preprint

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“…The optimization procedure minimizes the difference between the energy density resulting from the discrete interactions given by Eqs. 7and (8) and the Helfrich energy density,…”

Section: Methodsmentioning

confidence: 99%

“…Considering length-and timescales involved in biological processes, coarse-graining has become an essential approach in membrane simulations 6,7 . Interacting particle reaction-dynamics (iPRD) models 8 are extremely coarse-grained models that have been used to simulate a wide variety of cellular signalling pathways 9,10 . In such simulations, systems containing proteins, lipids, and metabolites are modelled with particles large enough to represent whole proteins or a patch of membrane lipids 11 .…”

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confidence: 99%

Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models

Sadeghi

Noé

2020

Nat Commun

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Biomembranes are two-dimensional assemblies of phospholipids that are only a few nanometres thick, but form micrometre-sized structures vital to cellular function. Explicit molecular modelling of biologically relevant membrane systems is computationally expensive due to the large number of solvent particles and slow membrane kinetics. Coarse-grained solventfree membrane models offer efficient sampling but sacrifice realistic kinetics, thereby limiting the ability to predict pathways and mechanisms of membrane processes. Here, we present a framework for integrating coarse-grained membrane models with continuum-based hydrodynamics. This framework facilitates efficient simulation of large biomembrane systems with large timesteps, while achieving realistic equilibrium and non-equilibrium kinetics. It helps to bridge between the nanometer/nanosecond spatiotemporal resolutions of coarse-grained models and biologically relevant time-and lengthscales. As a demonstration, we investigate fluctuations of red blood cells, with varying cytoplasmic viscosities, in 150-milliseconds-long trajectories, and compare kinetic properties against single-cell experimental observations.

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“…In particular, we decompose the system dynamics into di usion in the bound state, unbinding, di usion in the unbound state, and binding. Particle-based Brownian dynamics simulations (25) are used to obtain an equilibrium ensemble of configurations for the system when in the bound state. These configurations are then combined with Monte Carlo sampling of unbinding events to calculate the probability of unbinding in the crowded solution.…”

Section: Quasi-reversible Particle-based Reaction Dynamicsmentioning

confidence: 99%

“…To validate the proposed algorithm we compare the results from the quasi-reversible method with results from explicit simulations of the reversible reaction using the software package Readdy2 (25). We consider two scenarios for validation.…”

Section: Validation Of Quasi-reversible Simulationsmentioning

confidence: 99%

Concentration Sensing in Crowded Environments

Stroberg

Schnell

2020

Preprint

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Signal transduction within crowded cellular compartments is essential for the physiological function of cells and organisms. While the accuracy with which receptors can probe the concentration of ligands has been thoroughly investigated in dilute systems, the effect of macromolecular crowding on the inference of concentration remains unknown. In this work we develop a novel algorithm to simulate reversible reactions between reacting Brownian particles. This facilitates the calculation of reaction rates and correlation times for ligand-receptor systems in the presence of macromolecular crowding. Using this method, we show that it is possible for crowding to increase the accuracy of estimated ligand concentration based on receptor occupancy. In particular, we find that crowding can enhance the effective association rates between small ligands and receptors to a large enough degree to overcome the increased chance of rebinding due to caging by crowding molecules. For larger ligands, crowding decreases the accuracy of the receptor’s estimate primarily by decreasing the microscopic association and dissociation rates.SIGNIFICANCEDeveloping an understanding of how cells effectively transmit signals within or between compartments under physical constraints is an important challenge for biophysics. This work investigates the effect that macromolecular crowding can have on the accuracy of a simple ligand-receptor signaling system. We show that the accuracy of an inferred ligand concentration based on the occupancy of the receptor can be enhanced by crowding under certain circumstances. Additionally, we develop a simulation algorithm that speeds the calculation of reaction rates in crowded environments and can be readily applied to other, more complex systems.

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

Cited by 69 publications

References 79 publications

Intrinsic disorder in the T cell receptor creates cooperativity and controls ZAP70 binding

Intrinsic disorder in the T cell receptor creates cooperativity and controls ZAP70 binding

Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models

Concentration Sensing in Crowded Environments

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