From Continuum Fokker-Planck Models to Discrete Kinetic Models
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Two theoretical formalisms are widely used in modeling mechanochemical systems such as protein motors: continuum Fokker-Planck models and discrete kinetic models. Both have advantages and disadvantages. Here we present a "finite volume" procedure to solve Fokker-Planck equations. The procedure relates the continuum equations to a discrete mechanochemical kinetic model while retaining many of the features of the continuum formulation. The resulting numerical algorithm is a generalization of the algorithm developed previously by Fricks, Wang, and Elston through relaxing the local linearization approximation of the potential functions, and a more accurate treatment of chemical transitions. The new algorithm dramatically reduces the number of numerical cells required for a prescribed accuracy. The kinetic models constructed in this fashion retain some features of the continuum potentials, so that the algorithm provides a systematic and consistent treatment of mechanical-chemical responses such as load-velocity relations, which are difficult to capture with a priori kinetic models. Several numerical examples are given to illustrate the performance of the method.
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Quantitative Study of the Chiral Organization of the Phage Genome Induced by the Packaging Motor.
Cruz B, Zhu Z, Calderer C, Arsuaga J, Vazquez M Biophys J. 2020; 118(9):2103-2116.
PMID: 32353255 PMC: 7203069. DOI: 10.1016/j.bpj.2020.03.030.
Thermal fracture kinetics of heterogeneous semiflexible polymers.
Lorenzo A, De La Cruz E, Koslover E Soft Matter. 2020; 16(8):2017-2024.
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Theory of long binding events in single-molecule-controlled rotation experiments on F-ATPase.
Volkan-Kacso S, Marcus R Proc Natl Acad Sci U S A. 2017; 114(28):7272-7277.
PMID: 28652332 PMC: 5514755. DOI: 10.1073/pnas.1705960114.
Bhaban S, Materassi D, Li M, Hays T, Salapaka M PLoS Comput Biol. 2016; 12(11):e1005152.
PMID: 27812098 PMC: 5094777. DOI: 10.1371/journal.pcbi.1005152.