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Masterarbeit_main.bbl
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@article{Berry2002,
abstract = {Conventional equations for enzyme kinetics are based on mass-action laws, that may fail in low-dimensional and disordered media such as biological membranes. We present Monte Carlo simulations of an isolated Michaelis-Menten enzyme reaction on two-dimensional lattices with varying obstacle densities, as models of biological membranes. The model predicts that, as a result of anomalous diffusion on these low-dimensional media, the kinetics are of the fractal type. Consequently, the conventional equations for enzyme kinetics fail to describe the reaction. In particular, we show that the quasi-stationary-state assumption can hardly be retained in these conditions. Moreover, the fractal characteristics of the kinetics are increasingly pronounced as obstacle density and initial substrate concentration increase. The simulations indicate that these two influences are mainly additive. Finally, the simulations show pronounced S-P segregation over the lattice at obstacle densities compatible with in vivo conditions. This phenomenon could be a source of spatial self organization in biological membranes.},
author = {Berry, Hugues},
doi = {10.1016/S0006-3495(02)73953-2},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Berry - 2002 - Monte carlo simulations of enzyme reactions in two dimensions fractal kinetics and spatial segregation.pdf:pdf},
isbn = {0006-3495},
issn = {00063495},
journal = {Biophysical journal},
number = {4},
pages = {1891--1901},
pmid = {12324410},
publisher = {Elsevier},
title = {{Monte carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation.}},
url = {http://dx.doi.org/10.1016/S0006-3495(02)73953-2},
volume = {83},
year = {2002}
}
@article{Craigmile2003,
abstract = {We demonstrate that the fast and exact Davies–Harte algorithm is valid for simulating a certain class of stationary Gaussian processes – those with a negative autocovariance sequence for all non-zero lags. The result applies to well known classes of long memory processes: Gaussian fractionally differenced (FD) processes, fractional Gaussian noise (fGn) and the nonstationary fractional Brownian Motion (fBm).},
author = {Craigmile, Peter F.},
doi = {10.1111/1467-9892.00318},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Craigmile - 2003 - Simulating a class of stationary Gaussian processes using the Davies-Harte algorithm, with application to long memory.pdf:pdf},
issn = {0143-9782},
journal = {Journal of Time Series Analysis},
keywords = {Circulant embedding,Davies-Harte algorithm,Long memory process,Negative autocovariance sequence,Simulation,Time series analysis},
number = {5},
pages = {505--511},
title = {{Simulating a class of stationary Gaussian processes using the Davies-Harte algorithm, with application to long memory processes}},
volume = {24},
year = {2003}
}
@article{Echeverria2015,
author = {Echeverria, Carlos and Kapral, Raymond},
doi = {10.1039/C5CP05056A},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Echeverria, Kapral - 2015 - Enzyme kinetics and transport in a system crowded by mobile macromolecules.pdf:pdf},
issn = {1463-9076},
journal = {Phys. Chem. Chem. Phys.},
number = {43},
pages = {29243--29250},
publisher = {Royal Society of Chemistry},
title = {{Enzyme kinetics and transport in a system crowded by mobile macromolecules}},
url = {http://xlink.rsc.org/?DOI=C5CP05056A},
volume = {17},
year = {2015}
}
@article{Hofling2013,
author = {H{\"{o}}fling, Felix and Franosch, Thomas},
doi = {10.1088/0034-4885/76/4/046602},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/H{\"{o}}fling, Franosch - 2013 - Anomalous transport in the crowded world of biological cells.pdf:pdf},
issn = {0034-4885},
journal = {Reports on Progress in Physics},
month = {apr},
number = {4},
pages = {046602},
title = {{Anomalous transport in the crowded world of biological cells}},
url = {http://stacks.iop.org/0034-4885/76/i=4/a=046602?key=crossref.d72b9b76244e9222284e073065248855},
volume = {76},
year = {2013}
}
@phdthesis{Johannesschoneberg2014,
abstract = {We can see the faintest stars because rod cells in our eyes can detect single photons reliably and convert them reproducibly into an output current. Visual rhodopsin molecules respond to photon absorption by a change of their shape that sends a signal to other proteins. But how does this signal transduction cascade proceed in detail? How are the individual copies of all involved proteins orchestrated in space and time to give rise to cellular output? Experiments cannot simultaneously probe localizations and time sequences of all relevant molecular processes. A solution is to inte- grate experimental data in physically realistic computer models and simulating the spatiotemporal mechanism of signal transduction. The most detailed reaction kinetics simulation techniques are particle- based reaction-diffusion (PBRD) simulations. Here all molecules are represented as individual particles. Their diffusive motion and the reactions between them are simulated explicitly in space and time. However, existing PBRD techniques lack interaction potentials between particles that are needed to realistically model molecular aggregates, clusters or fibers/chains. Here a new class of reaction kinetics models is introduced that combines PBRD with interaction potentials. ReaDDy, a generic and platform-independent software package, has been developed to imple- ment this new class. ReaDDy has a modular and extensible software design, enabling straightforward implementations for different hard- ware (e.g. single-CPU, multithreading, GPU), and the incorporation of different models of particle dynamics (e.g. Langevin, overdamped Langevin, Metropolis Monte Carlo). Arbitrary particle interaction potentials (e.g. space exclusion, electrostatic interaction), and var- ious cellular geometries (e.g. disc membranes or vesicles) can be user-defined. ReaDDy was used to shed light on the spatiotemporal details of photoactivation in rod cell disc membranes. While the supramolecular architecture of rhodopsin (R) is controversial, it was shown here that various R-architectures are consistent with kinetic activation experi- ments performed by our experimental collaborators at Charit{\'{e}} (Berlin). Important mechanistic insights were produced, including: (1) The rate- limiting molecular steps in G-protein activation were identified. (2) Unproductive complexes between inactive R and G may exist, but their lifetime is limited to the 100 microseconds timescale. (3) Supramolecular structures of R (as opposed to uniformly distributed individual Rs) do not increase the speed of the activation kinetics. Such structures are likely to play an other regulatory role in the cascade. Simultaneously, experimentalists at Caesar (Bonn) have found new evidence of a specific and regular supramolecular structure, in which rhodopsin forms ’tracks’, i.e. double rows of dimers of approximately uniform length. A ReaDDy model confirms that this architecture is consistent with kinetic measurements, but also reveals a new regula- tion mechanism: The spatially separate and uniform track structures of R, combined with short-lived inactive R-G-precomplexes of R and G, lead to a time-scale separation of fast intra-track diffusion and activation and slow inter-track diffusion. As a result, the G-activation kinetics is biphasic, with a quick activation burst of {\~{}}4 G-proteins associated to one track. The subsequent slow activation phase is insensitive to the exact shutoff time of rhodopsin, thus ensuring a reliable output. While this insight from simulations must be confirmed experimentally, it may be an important component of single-photon response uniformity. The concepts and software developed in this thesis are not limited to rod cell phototransduction, but represent a general contribution towards a new generation of quantitative biology using physically real- istic models. In the future, together with super-resolution microscopy and single-molecule experiments, they could provide the foundation to reach for the stars in ’cellular dynamics’: Being able to simulate an entire cell.},
author = {Johannes sch{\"{o}}neberg},
file = {:home/mi/janekg89/Downloads/Schoeneberg{\_}dissertation{\_}compressed (2).pdf:pdf},
isbn = {9788578110796},
issn = {19454589},
pages = {162},
title = {{REACTION-DIFFUSION DYNAMICS IN BIOLOGICAL SYSTEMS}},
year = {2014}
}
@article{Schnell2004,
abstract = {We review recent evidence illustrating the fundamental difference between cytoplasmic and test tube biochemical kinetics and thermodynamics, and showing the breakdown of the law of mass action and power-law approximation in in vivo conditions. Simulations of biochemical reactions in non-homogeneous media show that as a result of anomalous diffusion and mixing of the biochemical species, reactions follow a fractal-like kinetics. Consequently, the conventional equations for biochemical pathways fail to describe the reactions in in vivo conditions. We present a modification to fractal-like kinetics following the Zipf-Mandelbrot distribution which will enable the modelling and analysis of biochemical reactions occurring in crowded intracellular environments. ?? 2004 Elsevier Ltd. All rights reserved.},
author = {Schnell, S. and Turner, T. E.},
doi = {10.1016/j.pbiomolbio.2004.01.012},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Schnell, Turner - 2004 - Reaction kinetics in intracellular environments with macromolecular crowding Simulations and rate laws.pdf:pdf},
isbn = {4418652868},
issn = {00796107},
journal = {Progress in Biophysics and Molecular Biology},
keywords = {Enzymatic reactions,Fractal-like kinetics,Intracellular environment,Macromolecular crowding,Reaction rate},
number = {2-3},
pages = {235--260},
pmid = {15142746},
title = {{Reaction kinetics in intracellular environments with macromolecular crowding: Simulations and rate laws}},
volume = {85},
year = {2004}
}
@article{Turner2004,
abstract = {In recent years, stochastic modelling has emerged as a physically more realistic alternative for modelling in vivo reactions. There are numerous stochastic approaches available in the literature; most of these assume that observed random fluctuations are a consequence of the small number of reacting molecules. We review some important developments of the stochastic approach and consider its suitability for modelling intracellular reactions. We then describe recent efforts to include the fluctuation effects caused by the structural organisation of the cytoplasm and the limited diffusion of molecules due to macromolecular crowding. ?? 2004 Elsevier Ltd. All rights reserved.},
author = {Turner, T. E. and Schnell, S. and Burrage, K.},
doi = {10.1016/j.compbiolchem.2004.05.001},
file = {:home/mi/janekg89/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Turner, Schnell, Burrage - 2004 - Stochastic approaches for modelling in vivo reactions.pdf:pdf},
isbn = {1476-9271 (Print)$\backslash$r1476-9271 (Linking)},
issn = {14769271},
journal = {Computational Biology and Chemistry},
keywords = {??-leap method,Fractal-like kinetics,Intracellular reactions,Quasi-steady-state approximation,Stochastic simulation algorithm},
number = {3},
pages = {165--178},
pmid = {15261147},
title = {{Stochastic approaches for modelling in vivo reactions}},
volume = {28},
year = {2004}
}