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Data-Driven Multiscale Modeling of Self-Assembly and Hierarchical Structural Formation in Biological Macro-Molecular Systems: Pyruvate Dehydrogenase Complex

In: High Performance Computing in Science and Engineering '22

Author

Listed:
  • P. N. Depta

    (Hamburg University of Technology, Institute of Solids Process Engineering and Particle Technology)

  • Maksym Dosta

    (Hamburg University of Technology, Institute of Solids Process Engineering and Particle Technology)

  • S. Heinrich

    (Hamburg University of Technology, Institute of Solids Process Engineering and Particle Technology)

Abstract

Macro-molecular self-assembly and hierarchical structural formation are crucial for a variety of systems in nature and technology. Especially biological systems often rely on a specific structural organization to enable their function. Examples are multi-enzyme complexes enabling catalytic activity through structure-based phenomena such as metabolic channeling or the self-assembly of virus capsids necessary for transport of the genetic material and overall infection process. This project attempts to improve understanding and modeling capabilities of such systems by developing a multiscale modeling methodology for self-assembly on the scales of micro-meters and milli-second including a data-driven parameterization approach. As model systems the hepatitis B core antigen (HBcAg) and pyruvate dehydrogenase complex (PDC) are used, which feature a macro-molecular self-assembly crucial in enabling their function.

Suggested Citation

  • P. N. Depta & Maksym Dosta & S. Heinrich, 2024. "Data-Driven Multiscale Modeling of Self-Assembly and Hierarchical Structural Formation in Biological Macro-Molecular Systems: Pyruvate Dehydrogenase Complex," Springer Books, in: Wolfgang E. Nagel & Dietmar H. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering '22, pages 355-370, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-46870-4_23
    DOI: 10.1007/978-3-031-46870-4_23
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