DC FieldValueLanguage
dc.contributor.authorDepta, Philipp Nicolas-
dc.contributor.authorJandt, Uwe-
dc.contributor.authorDosta, Maksym-
dc.contributor.authorZeng, An-Ping-
dc.contributor.authorHeinrich, Stefan-
dc.date.accessioned2019-03-13T13:05:52Z-
dc.date.available2019-03-13T13:05:52Z-
dc.date.issued2019-01-28-
dc.identifier.citationJournal of chemical information and modeling 1 (59): 386-398 (2019-01-28)de_DE
dc.identifier.issn1549-9596de_DE
dc.identifier.urihttp://hdl.handle.net/11420/2152-
dc.description.abstractMost processes involved in biological and biotechnological systems spread over many scales in space and time. For example, the interaction of multiple enzymes in heterogeneous enzymatic agglomerates or clusters, necessary for efficient enzymatic conversion, is of high interest for research and enzyme engineering. In order to understand and predict their overall behavior and performance, it is important to describe these scales as completely as possible, known as multiscale modeling. While many different approaches have been presented in recent years, knowledge about protein formation and bioagglomeration at the micro scale is still very limited. In an attempt to address such systems, we propose a bottom- up multiscale modeling methodology, bridging the gaps between molecular dynamics (MD) with an explicit solvent and the larger scale discrete element method (DEM) using an implicit solvent and abstracting macromolecules (e.g., proteins) as objects with anisotropic properties. We term this approach the molecular discrete element method (MDEM). For this, we present an orientation-sensitive diffusion model for DEM, which describes the dynamics of anisotropic translational and rotational diffusion, while implicitly considering solvent molecules and enforcing a canonical ensemble. A general-purpose model and parametrization approach is presented, which can be used to simulate any process involving diffusion of discrete particles. Effects of temperature and viscosity changes can be considered, and guidance is provided concerning time step selection. This model is generally applicable and serves as a precondition to enforce the proper dynamics (i.e., diffusion characteristics and canonical ensemble, similar to a thermostat in MD) for the proposed multiscale modeling methodology with anisotropic properties. Thereby, it presents a first step toward modeling at the micro scale and is integral to enforcing dynamics of such systems and therefore extensively validated. As a next step, interaction models are to be defined and added to the presented model. In comparison to atomistic and coarse-grained (CG) MD, a speedup of 5-7 orders of magnitude can be achieved. The approach is demonstrated on multiple components of the pyruvate dehydrogenase enzyme complex, a multienzymatic machinery that involves very different types of enzymes and is of high value to further elucidate the mechanisms of bioagglomeration and metabolic channeling.en
dc.description.sponsorshipThe authors gratefully acknowledge the German Research Foundation (DFG) for financial support (HE 4526/19-1 for authors from SPE and ZE 542/12-1 for authors from IBB within the priority program SPP 1934), as well as German Federal Ministry of Education and Research (BMBF, Grant 031B0222).de_DE
dc.language.isoende_DE
dc.relation.ispartofJournal of chemical information and modelingde_DE
dc.titleToward Multiscale Modeling of Proteins and Bioagglomerates: An Orientation-Sensitive Diffusion Model for the Integration of Molecular Dynamics and the Discrete Element Methodde_DE
dc.typeArticlede_DE
dc.type.diniarticle-
dcterms.DCMITypeText-
tuhh.abstract.englishMost processes involved in biological and biotechnological systems spread over many scales in space and time. For example, the interaction of multiple enzymes in heterogeneous enzymatic agglomerates or clusters, necessary for efficient enzymatic conversion, is of high interest for research and enzyme engineering. In order to understand and predict their overall behavior and performance, it is important to describe these scales as completely as possible, known as multiscale modeling. While many different approaches have been presented in recent years, knowledge about protein formation and bioagglomeration at the micro scale is still very limited. In an attempt to address such systems, we propose a bottom- up multiscale modeling methodology, bridging the gaps between molecular dynamics (MD) with an explicit solvent and the larger scale discrete element method (DEM) using an implicit solvent and abstracting macromolecules (e.g., proteins) as objects with anisotropic properties. We term this approach the molecular discrete element method (MDEM). For this, we present an orientation-sensitive diffusion model for DEM, which describes the dynamics of anisotropic translational and rotational diffusion, while implicitly considering solvent molecules and enforcing a canonical ensemble. A general-purpose model and parametrization approach is presented, which can be used to simulate any process involving diffusion of discrete particles. Effects of temperature and viscosity changes can be considered, and guidance is provided concerning time step selection. This model is generally applicable and serves as a precondition to enforce the proper dynamics (i.e., diffusion characteristics and canonical ensemble, similar to a thermostat in MD) for the proposed multiscale modeling methodology with anisotropic properties. Thereby, it presents a first step toward modeling at the micro scale and is integral to enforcing dynamics of such systems and therefore extensively validated. As a next step, interaction models are to be defined and added to the presented model. In comparison to atomistic and coarse-grained (CG) MD, a speedup of 5-7 orders of magnitude can be achieved. The approach is demonstrated on multiple components of the pyruvate dehydrogenase enzyme complex, a multienzymatic machinery that involves very different types of enzymes and is of high value to further elucidate the mechanisms of bioagglomeration and metabolic channeling.de_DE
tuhh.publisher.doi10.1021/acs.jcim.8b00613-
tuhh.publication.instituteFeststoffverfahrenstechnik und Partikeltechnologie V-3de_DE
tuhh.publication.instituteBioprozess- und Biosystemtechnik V-1de_DE
tuhh.publication.instituteMehrskalensimulation von Feststoffsystemen V-EXK1de_DE
tuhh.type.opus(wissenschaftlicher) Artikel-
tuhh.institute.germanBioprozess- und Biosystemtechnik V-1de
tuhh.institute.englishBioprozess- und Biosystemtechnik V-1de_DE
tuhh.gvk.hasppnfalse-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.issue1de_DE
tuhh.container.volume59de_DE
tuhh.container.startpage386de_DE
tuhh.container.endpage398de_DE
dc.relation.projectTeilprojekt von SPP 1934: Multiskalige modellgestützte Untersuchungen funktionaler Enzym- und Proteinagglomerate für biotechnologische Anwendung - Teil 2: Von der Struktur zur Funktion-
item.grantfulltextnone-
item.creatorGNDDepta, Philipp Nicolas-
item.creatorGNDJandt, Uwe-
item.creatorGNDDosta, Maksym-
item.creatorGNDZeng, An-Ping-
item.creatorGNDHeinrich, Stefan-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.creatorOrcidDepta, Philipp Nicolas-
item.creatorOrcidJandt, Uwe-
item.creatorOrcidDosta, Maksym-
item.creatorOrcidZeng, An-Ping-
item.creatorOrcidHeinrich, Stefan-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.deptFeststoffverfahrenstechnik und Partikeltechnologie V-3-
crisitem.author.deptBioprozess- und Biosystemtechnik V-1-
crisitem.author.deptMehrskalensimulation von Feststoffsystemen V-EXK1-
crisitem.author.deptBioprozess- und Biosystemtechnik V-1-
crisitem.author.deptFeststoffverfahrenstechnik und Partikeltechnologie V-3-
crisitem.author.orcid0000-0003-0579-5220-
crisitem.author.orcid0000-0001-8221-5176-
crisitem.author.orcid0000-0002-7578-8408-
crisitem.author.orcid0000-0001-9768-7096-
crisitem.author.orcid0000-0002-7901-1698-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.project.funderDeutsche Forschungsgemeinschaft (DFG)-
crisitem.project.funderid501100001659-
crisitem.project.funderrorid018mejw64-
crisitem.project.grantnoHE 4526/19-2-
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