Data for "Quantifying Dissipation in Actomyosin Networks"

Floyd, Carlos; Papoian, Garegin; Jarzynski, Christopher

Data for "Quantifying Dissipation in Actomyosin Networks"

dc.contributor.advisor	Papoian, Garegin
dc.contributor.advisor	Jaryzynski, Christopher
dc.contributor.author	Floyd, Carlos
dc.contributor.author	Papoian, Garegin
dc.contributor.author	Jarzynski, Christopher
dc.date.accessioned	2019-01-23T22:11:38Z
dc.date.available	2019-01-23T22:11:38Z
dc.date.issued	2019
dc.description	This is contains the source code and data set used for the paper "Quantifying Dissipation in Actomyosin Networks."	en_US
dc.description.abstract	Quantifying entropy production in various active matter phases would open new avenues for probing self-organization principles in these far-from-equilibrium systems. It has been hypothesized that the dissipation of free energy by active matter systems may be optimized to produce highly dissipative dynamical states, hence, leading to spontaneous emergence of more ordered states. This interesting idea has not been widely tested. In particular, it is not clear whether emergent states of actomyosin networks, which represent one of the most salient examples of biological active matter, self-organize following the principle of dissipa- tion optimization. In order to start addressing this question using detailed computational modeling, we rely on the MEDYAN simulation platform, which allows simulating active matter networks from fundamental molecular principles. We have extended the capabilities of MEDYAN to allow quantification of the rates of dissipation resulting from chemical re- actions and relaxation of mechanical stresses during simulation trajectories. This is done by computing precise changes in Gibbs free energy accompanying chemical reactions using a novel formula, and through detailed calculations of instantaneous values of the system’s mechanical energy. We validate our approach with a mean-field model that estimates the rates of dissipation from filament treadmilling. Applying this methodology to the self- organization of small disordered actomyosin networks, we find that compact and highly cross-linked networks tend to allow more efficient transduction of chemical free energy into mechanical energy. In these simple systems, we do not observe that spontaneous network reorganizations lead to increases in the total dissipation rate as predicted by the dissipation- driven adaptation hypothesis mentioned above. However, whether such a principle operates in more general, more complex cytoskeletal networks remains to be investigated.	en_US
dc.description.sponsorship	This work was supported by the following grants: * NSF 1632976 * NSF DMR-1506969 * NSF CHE-1800418	en_US
dc.description.uri	https://doi.org/10.1098/rsfs.2018.0078
dc.identifier	https://doi.org/10.13016/t8oa-9qra
dc.identifier.uri	http://hdl.handle.net/1903/21563
dc.language.iso	en_US	en_US
dc.relation.isAvailableAt	College of Computer, Mathematical & Natural Sciences	en_us
dc.relation.isAvailableAt	Physics	en_us
dc.relation.isAvailableAt	Digital Repository at the University of Maryland	en_us
dc.relation.isAvailableAt	University of Maryland (College Park, MD)	en_us
dc.subject	Dissipation, Actomyosin Networks, Actin Treadmilling, Network Percolation, Mean-Field Modeling, Active Matter	en_US
dc.title	Data for "Quantifying Dissipation in Actomyosin Networks"	en_US
dc.type	Dataset	en_US