EnzymAgglo - Multiscale model-based investigation of functional enzyme and protein agglomerates for biotechnological applications.Part 2: From structure to function

EnzymAgglo - 基于多尺度模型的生物技术应用功能酶和蛋白质聚集体研究。第 2 部分:从结构到功能

基本信息

项目摘要

The model based understanding of the structure defining processes of multi-enzymatic systems and protein agglomeration, as well as their relation to function (e.g., activity) has received increasing interest in recent years. With new multi-scaled modeling approaches and increased computational capabilities in recent years (especially GPUs), the detailed investigation and prediction of such macromolecular phenomena comes into reach. To achieve this, we developed a generally applicable multi-scale model framework, termed “Molecular discrete element method (MDEM)”, during the first project phase.Specifically, it focuses on the structural development of such systems depending on process conditions. It applies on the macro-molecular scale (ms and µm) and will be finalized in the remaining time of the first period of the project. The MDEM framework allows investigations of biologically and technically interesting structural phenomena due to its speedup of 5 to 7 orders of magnitude with respect to simulation time and/or scale in comparison to traditional MD. At the same time, it retains the necessary detail on the meso-scale through anisotropic consideration of properties. While, during the first project phase, the framework was established using the multi-enzymatic pyruvate dehydrogenase complex (PDC) as a model system, it has received very positive feedback from other SPP project partners for applications to numerous other processes and phenomena (e.g., protein absorption at the oil-water interface). Initial collaborations have been initiated and are planned to be intensified. The focus of the second project phase will lie on expansion of the MDEM approach with respect to the determination of function from structure; increased size and time scales; and application of developed framework to new processes in collaboration with SPP project partners. To achieve these goals, the MDEM framework will be coupled to population balance modeling (e.g., for experimental validation and parameter studies). Further, protein-protein and protein-interface interaction will be refined and extended to cover density effects (molecular crowding; diffusion limitation), and competetive interaction of multiple partners. Deduction from structure to function will be done by coupling MDEM to computational fluid dynamics / finite volume computation method, including spatially resolved enzymatic reaction and metabolite diffusion kinetics. A further abstraction will take place to enable higher-scale model (termed “MDEM-2”) and push towards the process scale: Stably connected units (e.g., the catalytic core of PDC) are abstracted as one particle and parameterized using the data from MDEM. Experimental feedback for catalytically active multi-enzymatic systems will be obtained in-house, while extensive collaborations with SPP project partners are developing and ongoing, allowing to refine and verify the MDEM(-2) approach on wide variety of process parameters.
近年来,对多酶系统和蛋白质聚集的结构定义过程及其与功能(如活性)的关系的基于模型的理解越来越受到人们的关注。近年来,随着新的多尺度建模方法和计算能力的增加(特别是图形处理器),对这种大分子现象的详细研究和预测成为可能。为了实现这一目标,我们在第一个项目阶段开发了一个普遍适用的多尺度模型框架,称为分子离散元方法(MDEM),具体而言,它侧重于根据工艺条件对这类系统的结构开发。它适用于大分子尺度(毫微米和微米),并将在项目第一阶段的剩余时间内完成。与传统的MD相比,MDEM框架在模拟时间和/或规模方面的速度提高了5到7个数量级,因此可以研究具有生物学和技术意义的结构现象。同时,通过对属性的各向异性考虑,它在介观尺度上保留了必要的细节。虽然在第一个项目阶段,该框架是使用多酶促丙酮酸脱氢酶复合体(PDC)作为模型系统建立的,但它已经从其他SPP项目伙伴那里收到了非常积极的反馈,用于许多其他过程和现象(例如,在油-水界面的蛋白质吸收)。初步协作已经启动,并计划加强。第二个项目阶段的重点将是扩大千年发展目标方法,从结构上确定职能;扩大规模和时间尺度;与战略计划项目合作伙伴合作,将已开发的框架应用于新的进程。为了实现这些目标,MDEM框架将与人口平衡建模相结合(例如,用于实验验证和参数研究)。此外,蛋白质-蛋白质和蛋白质-界面相互作用将得到改进和扩展,以涵盖密度效应(分子拥挤;扩散限制)和多个伙伴之间的竞争性相互作用。通过将MDEM与计算流体力学/有限体积计算方法相结合,完成从结构到功能的推导,包括空间分辨的酶反应和代谢物扩散动力学。将进行进一步的抽象,以实现更高比例尺的模型(称为“MDEM-2”)并推动过程规模:稳定连接的单元(例如,PDC的催化核心)被抽象为一个粒子,并使用来自MDEM的数据进行参数化。对催化活性多酶系统的实验反馈将在内部获得,同时与SPP项目合作伙伴的广泛合作正在开发和进行中,从而能够在各种工艺参数上改进和验证MDEM(-2)方法。

项目成果

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Professor Dr.-Ing. Stefan Heinrich其他文献

Professor Dr.-Ing. Stefan Heinrich的其他文献

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{{ truncateString('Professor Dr.-Ing. Stefan Heinrich', 18)}}的其他基金

Strategy development for the coating of open-pore structured, nanoporous materials with low density
低密度开孔结构纳米多孔材料涂层的策略开发
  • 批准号:
    408323810
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Micro-mechanics of wet solids in gas-solid contactors
气固接触器中湿固体的微观力学
  • 批准号:
    214351323
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Dynamics of spray granulation in continuously operated horizontal fluidised beds
连续运行水平流化床喷雾造粒动力学
  • 批准号:
    238434279
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
Coordination Funds
协调基金
  • 批准号:
    245108490
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
Central project: Dynamic simulation of interconnected processes
中心项目:互连过程的动态模拟
  • 批准号:
    238566663
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
Characterization of the fluid dynamics and discrete particle modelling of a novel spouted bed apparatus
新型喷动床装置的流体动力学和离散颗粒建模表征
  • 批准号:
    162490600
  • 财政年份:
    2010
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Membrane assisted fluidized bed reactor: Hydrodynamics, heat transfer and reactor demonstration
膜辅助流化床反应器:流体动力学、传热和反应器演示
  • 批准号:
    27255698
  • 财政年份:
    2006
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Membranes in fluidized bed for oxidation of hydrocarbons
流化床中用于碳氢化合物氧化的膜
  • 批准号:
    5341210
  • 财政年份:
    2001
  • 资助金额:
    --
  • 项目类别:
    Research Units
Spouted bed processing for structuring of conductive battery hetero-aggregates
用于导电电池异质聚集体结构化的喷动床加工
  • 批准号:
    462397288
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
Investigation of Chemical Looping Combustion with a novel two stage fuel reactor for reduction of CO2 emissions
研究采用新型两级燃料反应堆进行化学循环燃烧以减少二氧化碳排放
  • 批准号:
    495012431
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants

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职业:植物叶片细胞形态发生和组织发育的多尺度模型
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Multiscale Computational Microscopy of HIV-1
HIV-1 的多尺度计算显微镜
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    10756808
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EAR-PF: A Multiscale Seismic Velocity Model for the Gulf of Alaska
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病毒感染中宿主细胞多尺度动力学的模型驱动研究
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High-throughput Phenotyping of iPSC-derived Airway Epithelium by Multiscale Machine Learning Microscopy
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