ArticleThe Journal of chemical physics2013
A computational kinetic model of diffusion for molecular systems.
Article in The Journal of chemical physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Unifying Single-Channel Permeability From Rare-Event Sampling and Steady-State Flux.Frontiers in molecular biosciences · 2022Article
- Hybrid finite element and Brownian dynamics method for charged particles.The Journal of chemical physics · 2016Article
- Theoretical frameworks for multiscale modeling and simulation.Current opinion in structural biology · 2014Review
- Markov state models of biomolecular conformational dynamics.Current opinion in structural biology · 2014Review
- Perspective: Reaches of chemical physics in biology.The Journal of chemical physics · 2013Article
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2 authors.
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Abstract
Regulation of biomolecular transport in cells involves intra-protein steps like gating and passage through channels, but these steps are preceded by extra-protein steps, namely, diffusive approach and admittance of solutes. The extra-protein steps develop over a 10-100 nm length scale typically in a highly particular environment, characterized through the protein's geometry, surrounding electrostatic field, and location. In order to account for solute energetics and mobility of solutes in this environment at a relevant resolution, we propose a particle-based kinetic model of diffusion based on a Markov State Model framework. Prerequisite input data consist of diffusion coefficient and potential of mean force maps generated from extensive molecular dynamics simulations of proteins and their environment that sample multi-nanosecond durations. The suggested diffusion model can describe transport processes beyond microsecond duration, relevant for biological function and beyond the realm of molecular dynamics simulation. For this purpose the systems are represented by a discrete set of states specified by the positions, volumes, and surface elements of Voronoi grid cells distributed according to a density function resolving the often intricate relevant diffusion space. Validation tests carried out for generic diffusion spaces show that the model and the associated Brownian motion algorithm are viable over a large range of parameter values such as time step, diffusion coefficient, and grid density. A concrete application of the method is demonstrated for ion diffusion around and through the Eschericia coli mechanosensitive channel of small conductance ecMscS.
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