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Browsing by Subject "Drug"

Now showing 1 - 2 of 2
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    Comparing classification vs. continuum models of the structure of substance dependence and abuse.
    (2009-12) Vrieze, Scott Ian
    Substance use disorders are classified as categorical disorders by prominent nosologies [1]. A bevy of structural equation models have suggested dimensional solutions to drug dependence and abuse criteria. However, it is well known that factor models can fit categorical structures, and class models can fit dimensional structures. Recent research has thus compared relative fits of both latent class and trait models, and in some cases mixtures of latent traits. Results have been inconsistent, in large part due to the level of analysis. We attend to both problems by fitting models in a large sample with high base rates of alcohol, marijuana, cocaine, and stimulant disorders, allowing us to fit complex models both at fine and coarse levels of analysis (e.g., only alcohol items versus all items from a variety of drug classes). In general, dependence and abuse items from different drug classes can be modeled with drug-specific factors, one per drug. When more complex models are fit only to alcohol items, the best fitting model is a mixture of latent traits that maps closely onto DSM-IV-TR [1] nosology.
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    Multi-Scale Modeling of Microtubule Dynamics and the Regulation by Microtubule-Targeting Agents
    (2020-01) Hemmat, Mahya
    Microtubules (MTs) serve to facilitate vital cellular functions, such as chromosome segregation during mitosis and synaptic plasticity. MTs self-assemble via “dynamic instability,” in which the dynamic plus ends switch stochastically between alternating phases of polymerization and depolymerization. A key question in the field is what are the atomistic origins of this switching, i.e., what is different between the GTP- and GDP-tubulin states that enables MT growth and shortening, respectively? More generally, MTs are a great example of a complex biological system with spatial and temporal scales ranging from atomistic interactions such as GTP hydrolysis to cell-level behavior such as response to MT dynamics during mitotic progression. To understand a complex biological system behavior, a key challenge is connecting together the vast range of theoretical frameworks across length- and time scales. At the same time, MT interactions with associated proteins and binding agents, such as chemotherapy drugs, can strongly affect this dynamic process through molecular mechanisms that remain to be elucidated. The work in this dissertation integrates multiscale computational modeling with high resolution experimental observations to understand the molecular mechanism underlying MT dynamic instability and the regulation of dynamics by a well-established microtubule-targeting agent (MTA), colchicine. First, we develop a multi-scale modeling framework in which molecular dynamics (MD) are performed to investigate the interaction potential energies of tubulin-tubulin heterodimers, then, those results will be incorporated into Brownian dynamics (BD) simulations to study the kinetics of dimers assembly into MT lattice, and finally, thermo-kinetic and mechanochemical modeling of MT assembly, with inputs from MD and BD simulations, provide an insight into individual MT dynamics and details about MT tip structures. The model results point to a nucleotide-independent lateral bond of ~4 kBT, a nucleotide-dependent longitudinal bond of ~9 and ~5 kBT (∆∆G_long^0≈ 4 kBT) for GTP- and GDP-dimers, respectively and a radial bending angle preference (~1.5 kBT) for GDP-dimers. Furthermore, the framework informs us on how a well-known MTA, colchicine, affects MT dynamics. We found that colchicine binds mainly to free tubulin and sub-stoichiometrically poisons the end of protofilaments (PFs) through a copolymerization mechanism by which tubulin-colchicine (TC) complexes reduce the affinity of the PF for further tubulin addition and reinforce tubulin-tubulin lateral bond, a mechanism entirely distinct from that of paclitaxel or vinblastine.. In summary, this dissertation advances our knowledge about the molecular mechanism that drives dynamic instability and its regulation by MTAs within the context of cellular biology through a multi-scale approach and can be used for the development of more effective cancer therapeutic agents.