Data-driven multiscale modeling of self-assembly and hierarchical structural formation in biological macro-molecular systems: pyruvate dehydrogenase complex

Start Page
355
End Page
370
Citation
High Performance Computing in Science and Engineering ’22: Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2022: 355-370 (2024)
Publisher DOI
10.1007/978-3-031-46870-4_23
Scopus ID
2-s2.0-85152161586
Publisher
Springer
ISBN
978-3-031-46870-4
978-3-031-46869-8
978-3-031-46871-1
978-3-031-46872-8
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.
DDC Class
600: Technology