Book ChapterDOI
Large multiprotein structures modeling and simulation: the need for mesoscopic models.
TLDR
3DSPI is presented, a model dedicated to studies of nuclear bodies based on a simple formalism inspired from molecular dynamics and coarse-grained models: particles interacting through a potential energy function and driven by an overdamped Langevin equation.Abstract:
Recent observational techniques based upon confocal microscopy make it possible to observe cells at a scale that has never been probed before: the mesoscopic scale. In the eukaryotic cell nucleus, many objects demonstrating phenomena occurring at this scale, such as nuclear bodies, are current subjects of investigations. But from a modeling perspective, this scale has not been widely explored, and hence there is a lack of suitable models for such studies. By reviewing higher and lower scale modeling techniques, we analyze their relevance in the context of mesoscale phenomena. We emphasize important characteristics that should be included in a mesoscopic model: an explicit continuous three-dimensional space with discrete simplified molecules that still have the characteristics of steric volume exclusion and realistic distant interaction forces. Then we present 3DSPI, a model dedicated to studies of nuclear bodies based on a simple formalism inspired from molecular dynamics and coarse-grained models: particles interacting through a potential energy function and driven by an overdamped Langevin equation. Finally, we present the features expected to be included in the model, pointing out the difficulties that might arise.read more
Citations
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Journal ArticleDOI
Coarse-Grained Protein Models and Their Applications
Sebastian Kmiecik,Dominik Gront,Michal Kolinski,Lukasz Wieteska,Lukasz Wieteska,Aleksandra Elzbieta Dawid,Andrzej Kolinski +6 more
TL;DR: An overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions are provided.
Journal ArticleDOI
Multiagent simulation of evolutive plate tectonics applied to the thermal evolution of the Earth
M. Combes,C. Grigne,Laurent Husson,Clinton P. Conrad,S. Le Yaouanq,Marc Parenthoën,C. Tisseau,Jacques Tisseau +7 more
TL;DR: In this paper, a MACMA model was designed to simulate time-dependent plate tectonics in a 2D cylindrical geometry with evolutive plate boundaries, based on multiagent systems that express thermal and mechanical interactions.
Journal ArticleDOI
Multiscale multiagent architecture validation by virtual instruments in molecular dynamics experiments
TL;DR: The method is applied to classical situations, such as the Joule-Gay Lussac experiment or the maxwellian relaxation in a hard-sphere gas, and the simulated gas behavior is in good agreement with theoretical results for gases without interaction.
Dissertation
Stochasticité de l'expression génique et régulation transcriptionnelle -- Modélisation de la dynamique spatiale et temporelle des structures multiprotéiques
TL;DR: Pour l'etude des phenomenes d'organisation mesoscopique au sein du noyau cellulaire, nous proposons un modele de simulation "4D" (integrant l'espace et le temps) yn d'etudier specifiquement the dynamique stochastique de the regulation transcriptionnelle.
Dissertation
Étude des mécanismes de refroidissement du manteau terrestre simulés par des systèmes multi-agents
TL;DR: The modele MACMA (MAnteau Convectif Multi-Agents) as discussed by the authors simule a tectonique variable dans le temps, avec des frontieres de plaques mobiles dans a geometrie cylindrique 2D.
References
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Wendy D. Cornell,Piotr Cieplak,Piotr Cieplak,Christopher I. Bayly,Christopher I. Bayly,Ian R. Gould,Ian R. Gould,Kenneth M. Merz,Kenneth M. Merz,David M. Ferguson,David M. Ferguson,David C. Spellmeyer,David C. Spellmeyer,Thomas R. Fox,James W. Caldwell,Peter A. Kollman +15 more
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Journal ArticleDOI
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Journal ArticleDOI
Macromolecular crowding: obvious but underappreciated.
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Journal ArticleDOI
Noise in eukaryotic gene expression
TL;DR: It is shown that stochasticity (noise) arising from transcription contributes significantly to the level of heterogeneity within a eukaryotic clonal population, in contrast to observations in prokaryotes, and that such noise can be modulated at the translational level.