Glycolysis: thermodynamics and pathway predictions

糖酵解：热力学和途径预测

基本信息

批准号：
316870850
负责人：
Privatdozent Dr.-Ing. Christoph Held
金额：
--
依托单位：
Lehrstuhl für Allgemeine Physikalische Chemie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2021-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/316870850?language=en
关键词：
Glycolysis thermodynamics pathway predictions

项目摘要

The application of thermodynamics with published models still does not allow satisfactory predictions of the feasibility of biochemical pathways. This is due to the fact that basic data are either not published in the literature so far or available data is very inaccurate (group contribution methods). These basic data include thermodynamic data for pure metabolites as well as data on reaction equilibria. The latter depend on a number of parameters (e.g., pH, temperature, composition of the reaction medium in the cytoplasm). These data are included in rigorous models that depict metabolic pathways mathematically. To make these models more predictive, accurate thermodynamic data on pure metabolites as well as on reaction equilibria must be available. Further, effects like molecular crowding must be considered to make metabolic networks better predictable. If such data were available, they would be applicable in mathematical models for the description of metabolic networks, similar to it what has already been reached for systems of comparable complexity (e.g., petroleum refineries).This project aims to use new thermodynamic tools for the quantitative determination of properties of pure metabolites and reaction equilibria in order to predict the thermodynamics of the metabolic pathways. Glycolysis is chosen for that purpose as especially thermodynamics of glycolysis is still not understood. In this proposal, in vitro studies are suggested that address complex interactions that are typical for living systems (presence of salts and molecular crowders). This will allow investigating their influence on the thermodynamics of metabolic reactions, a question that is strongly discussed in the community.In a first step, new basic data for selected metabolites and individual reactions within glycolysis will be determined. The influence of real conditions in the cytoplasm on these data will be investigated e.g., pH or composition of the cytoplasm. In a second step, the effects of bio-typical phenomena (species diversity, crowding) on thermodynamics and mass-flow calculations will be examined. This will finally show how consistent thermodynamic data can improve the predictive power of metabolic network calculations.To achieve the goal, thermochemistry, quantum chemistry and thermodynamics have to be combined with material flow analysis:- Verevkin: Determination and prediction of basic data of the pure metabolites- Held: Determination and prediction of the reaction equilibria of the individual reaction steps and under the influence of real cell conditions- Maskow: application of these data in simplified and real metabolic networks under non-equilibrium conditionsThe project results obtained will be applied in biotechnology (bioengineering, systems biology).

热力学与已发表模型的应用仍然无法对生化途径的可行性进行令人满意的预测。这是因为基础数据要么尚未在文献中发表，要么现有数据非常不准确（群体贡献法）。这些基本数据包括纯代谢物的热力学数据以及反应平衡数据。后者取决于许多参数（例如，pH、温度、细胞质中反应介质的组成）。这些数据包含在以数学方式描述代谢途径的严格模型中。为了使这些模型更具预测性，必须获得有关纯代谢物以及反应平衡的准确热力学数据。此外，必须考虑分子拥挤等效应，以使代谢网络更好地可预测。如果这些数据可用，它们将适用于描述代谢网络的数学模型，类似于具有相当复杂性的系统（例如炼油厂）已经达到的结果。该项目旨在使用新的热力学工具来描述代谢网络。定量测定纯代谢物的性质和反应平衡，以预测代谢途径的热力学。选择糖酵解就是为了这个目的，因为糖酵解的热力学仍然不清楚。在该提案中，建议进行体外研究来解决生命系统中典型的复杂相互作用（盐和分子拥挤的存在）。这将有助于研究它们对代谢反应热力学的影响，这是社区中强烈讨论的一个问题。第一步，将确定选定代谢物和糖酵解中各个反应的新基本数据。将研究细胞质中的实际条件对这些数据的影响，例如细胞质的 pH 值或组成。第二步，将研究生物典型现象（物种多样性、拥挤）对热力学和质量流量计算的影响。这最终将展示一致的热力学数据如何能够提高代谢网络计算的预测能力。为了实现这一目标，热化学、量子化学和热力学必须与物质流分析相结合：- Verevkin：纯物质基础数据的确定和预测代谢物 - 举行：在真实细胞条件的影响下确定和预测各个反应步骤的反应平衡 - Maskow：将这些数据在非平衡条件下的简化和真实代谢网络中应用所获得的项目结果将应用于生物技术（生物工程、系统生物学）。