9 research outputs found

    Water Chreodes and the Mechanisms of Ligand Diffusion, General Anesthesia, and Sleep

    Get PDF
    The concept of the presence of passageways, chreodes, created by the influence of the hydropathic states of amino acid side chains on the surface water of proteins, has been proposed. These chreodes facilitate and direct the diffusion of neurotransmitters through surface water, to the receptor or active site on a protein. This system of chreodes is vulnerable to the presence of some other molecules that may encounter the chreode system. This encounter and disruption has been proposed to explain the mechanism of general anesthesia. Based on much recent evidence of the similarities between anesthesia from volatile anesthetic agents and sleep, a comparable mechanism has been proposed for sleep. Since this must be an exogenous substance to be comparable to a general anesthetic agent, it was proposed that this exogenous, sleep-producing substance is elemental nitrogen. Recent evidence supports these hypotheses

    Hydration and thermal decomposition of cement/calcium-sulphate based materials

    Get PDF

    Meso-scale modeling of reaction-diffusion processes using cellular automata

    Get PDF

    Prédiction structurale de biomolécules à l'aide d'une construction d'automates cellulaires simulant la dynamique moléculaire

    Full text link
    Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

    A Cellular Automata Model of Enantiomer Interactions with beta-Cyclodextrin

    Get PDF
    The binding mechanisms of molecules to cyclodextrins continues to be studied to better explain the interactions occurring. The majority of published models focus on one-to-one molecular binding thermodynamics to explain experimental results. They rely on physical concepts of energies and forces to guide the actions of molecules expressed mathematically in terms of differential and non-linear equations. These models are limited in scope due to their complexity and are not easily expanded to study many diverse analytes. Conversely, cellular automata uses simple mathematical idealizations of systems governed by deterministic and probabilistic rules that are easily adaptable to many types of molecular interactions. The primary goal of this research is to develop a model that is easy to use in the prediction of beta-cyclodextrin chromatographic separations of enantiomers. The model uses variegated square cells to simulate the physical environment of the molecules involved, evolving by a series of discrete time-steps referred to as iterations. Governing probabilistic rules define the physical and chemical interactions. Rules are randomly applied to all the cells of the system during each iteration and the system is updated accordingly. Micro and macro visual analysis is possible in addition to statistical output. Results demonstrate the model’s capability to use probabilistic rules for breaking of analyte-to-cyclodextrin complexes that were correlated to published experimentally determined equilibrium constants. The model was further expanded to predict the strength of interactions between enantiomer pairs to beta-cyclodextrin and their potential separation. The model accurately predicted the order of strength for six enantiomer pairs. To truly predict chromatographic separation of enantiomers, the model was expanded from one-to-one interactions between enantiomers and beta-cyclodextrin to a larger modeled chromatographic scale. At this scale enantiomer separation was modeled and evaluated for peak resolution and selectivity while varying column temperature, mobile phase pH and flow, and injection volumes. All results agreed well with published laboratory results. With the cost of research and development increasing, ongoing budget cuts, and the rush to get products to market first, an analytical model that can run multiple chromatographic simulations in minutes versus days could prove a valuable tool to many industries

    Vormen van inzicht

    Get PDF

    A Cellular Automata Model of Water

    No full text
    corecore