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Non-native aggregation of alpha-chymotrypsinogen A from a combined experimental and modeling approach.

机译:通过组合的实验和建模方法,α-胰凝乳蛋白酶原A的非天然聚集。

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Non-native aggregation is the process in which protein monomers self-assemble into aggregates in which the constituent monomers have significantly non-native structure. These aggregates range in size and morphology, but are commonly rich in beta-sheet content. Non-native aggregates and their upstream intermediates have been implicated in a number of debilitating diseases including Alzheimer's, Huntington's, Parkinson's, and Creutzfield-Jacob disease. In the pharmaceutical industry, protein aggregation is one of the major impediments to rapid product development, affecting product purification, formulation, filling, shipment, storage, and delivery.;The mechanism of protein aggregation has been the focus of extensive research. In spite of this effort, details of the intermediate stages of protein aggregation typically remain elusive due to difficulties in experimentally isolating and characterizing the transient intermediates of the aggregation pathway. Mathematical models of protein aggregation provide a means to infer mechanistic details from experimental aggregation data. Knowledge of details of the aggregation mechanism can serve as a foundation for future approaches to predict aggregation rates and identify ways to rationally control aggregation processes.;A goal of this thesis is to develop a combined modeling and experimental approach to discern details of non-native protein aggregation mechanisms. The Lumry-Eyring nucleated polymerization (LENP) model was adapted from simpler extended Lumry-Eyring models and validated against experimental alpha-chymotrypsinogen aggregation data. An attractive feature of the LENP model is that its outputs are experimentally tractable quantities such as extent of conversion, average aggregate size, and aggregate size distribution as functions of time. Several distinguishing features of this model are: (1) it captures a variety of experimentally observed aggregation behaviors within the same model; (2) it self-consistently and simultaneously treats the contributions from unfolding, self-association, and growth; (3) it and its predecessor are the only models to treat the effects of aggregate solubility on observed kinetics.;The thermodynamics and kinetics of unfolding of the model protein alpha-chymotrypsinogen (aCgn) were monitored with differential scanning calorimetry, equilibrium and stopped-flow fluorescence, and circular dichroism (CD). Size exclusion chromatography, seeding experiments, CD, light scattering, isothermal and temperature-jump monomer loss, and calorimetry were used to probe different stages of aggregation. The data were analyzed self-consistently in terms of the LENP model.;Key results of the analysis are summarized here. Aggregation of aCgn can be described by a nucleated polymerization mechanism in which the irreversible structural conversion of monomers to beta-sheet either is part of or occurs soon after the rate-limiting step for locking monomers into aggregate. The observed aggregation rate coefficient and the nucleus size are highly temperature and protein concentration-dependent. The intrinsic aggregation rate coefficient has a negative activation energy that can be attributed to the nucleation step, while the intrinsic growth timescale is temperature-independent. Aggregate formation is enthalpically favored at elevated temperatures despite the highly repulsive electrostatics, and is inferred to be stabilized by hydrogen bonding and favorable enthalpic contributions involved in forming the beta-sheet aggregate structure.;The LENP model was successfully applied to determine details of the aCgn aggregation mechanism. The combined modeling and experimental approach developed and employed in this thesis is expected to be of general utility in interpreting aggregation behaviors for a broad range of experimental systems beyond alpha-chymotrypsinogen.
机译:非天然聚集是蛋白质单体自组装成聚集体的过程,其中组成单体具有明显的非天然结构。这些聚集体的大小和形态各不相同,但通常都富含β-折叠。非天然聚集体及其上游中间体与多种衰弱性疾病有关,包括阿尔茨海默氏病,亨廷顿氏病,帕金森氏病和克雅氏病。在制药工业中,蛋白质聚集是阻碍产品快速开发的主要障碍之一,影响产品的纯化,配制,填充,运输,储存和输送。蛋白质聚集的机理一直是广泛研究的重点。尽管进行了这种努力,但是由于在实验上分离和表征聚集途径的瞬时中间体的困难,蛋白质聚集的中间阶段的细节通常仍然难以捉摸。蛋白质聚集的数学模型提供了一种从实验聚集数据推断机理细节的方法。对聚集机制细节的了解可以为将来预测聚集速率和确定合理控制聚集过程的方法奠定基础。本论文的目的是开发一种组合模型和实验方法来识别非本地细节蛋白质聚集机制。 Lumry-Eyring有核聚合(LENP)模型改编自更简单的扩展Lumry-Eyring模型,并针对实验性α-胰凝乳蛋白酶原聚集数据进行了验证。 LENP模型的一个吸引人的特征是它的输出是实验上易于控制的量,例如转化程度,平均总粒度和总粒度分布随时间的变化。该模型的几个显着特征是:(1)它捕获了同一模型内各种实验观察到的聚集行为; (2)自洽一致,并同时对待发展,自我交往和成长的贡献; (3)它和它的前身是处理聚集体溶解度对观察到的动力学影响的唯一模型。;使用差示扫描量热法,平衡和停止监测了模型蛋白α-胰凝乳蛋白酶原(aCgn)展开的热力学和动力学。流荧光和圆二色性(CD)。尺寸排阻色谱,接种实验,CD,光散射,等温和温度跃变单体损失以及量热法用于探测聚集的不同阶段。根据LENP模型对数据进行了自洽的分析。总结了分析的主要结果。 aCgn的聚集可通过成核的聚合机理来描述,其中单体不可逆的结构转化为将单体锁定为聚集体的限速步骤的一部分或在其发生之后立即发生。观察到的聚集速率系数和细胞核大小高度依赖于温度和蛋白质浓度。本征聚集速率系数具有负活化能,该活化能可归因于成核步骤,而本征生长时间尺度与温度无关。尽管具有高度排斥性的静电,但在高温下聚集体的形成在焓上是有利的,并且可以推断是通过氢键和形成β-折叠聚集体结构所涉及的有利的焓贡献而得以稳定。聚集机制。本论文开发和采用的组合建模和实验方法有望在解释除α-胰凝乳蛋白酶原以外的广泛实验系统中的聚集行为方面具有通用性。

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