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Physics-Based and Data-Driven Multiscale Modeling of the Structural Formation in Macromolecular Systems

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Physics-Based and Data-Driven Multiscale Modeling of the Structural Formation in Macromolecular Systems (Band 25)

Philipp Nicolas Depta (Autor)

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In order to improve knowledge on macromolecular structural formation and self-assembly, this work proposes a physics-based and data-driven multiscale modeling framework capable of describing structural formation on micro-meter and milli-second scales near molecular-level precision. The framework abstracts macromolecules as anisotropic unit objects and models the interactions and environment using data-driven approaches. The models are parameterized in a bottom-up fashion and validated top-down by comparison with literature and collaborator data for self-assembly of three model system: alginate gelation, hepatitis B virus capsids, and the pyruvate dehydrogenase complex.

ISBN-13 (Printausgabe) 9783736979727
ISBN-13 (E-Book) 9783736969728
Sprache Englisch
Seitenanzahl 296
Umschlagkaschierung matt
Auflage 1.
Buchreihe SPE-Schriftenreihe
Band 25
Erscheinungsort Göttingen
Promotionsort TU Hamburg
Erscheinungsdatum 27.02.2024
Allgemeine Einordnung Dissertation
Fachbereiche Biochemie, Molekularbiologie, Gentechnologie
Biophysik
Maschinenbau und Verfahrenstechnik
Schlagwörter multiscale modeling, molecular modeling, Molecular Discrete Element Method, MDEM, Discrete Element Method, DEM, coarse-graining, Molecular Dynamics, MD, Langevin dynamics, machine learning, ML, supervised learning, Kriging, macromolecular self-assembly, structural formation simulation, anisotropic macromolecules, assembly pathways, assembly kinetics, molecular collisions, 6D intermolecular interaction potentials, specialized force-fields, molecular binding, bonded interaction, hepatitis B core antigen, HBcAg, capsid formation, virus-like particles, VLP, pyruvate dehydrogenase complex, PDC, alginate, alginic acid, biopolymer, gelation, gel, aerogel, porous nanomaterial, anisotropic diffusion, ion binding model, calcium, proteins, enzymes, multi-enzymatic biocatalysis, metabolic channeling, high performance computing, HLRS, GPU implementation, MUSEN