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Integrating HDX-MS and Molecular Dynamics to investigate the mechanism of activation of the RORy by multiple small molecule modulators

Integrating HDX-MS and Molecular Dynamics to investigate the mechanism of activation of the RORy by multiple small molecule modulators
整合 HDX-MS 和分子动力学研究多种小分子调节剂激活 RORy 的机制
批准号:
2736597
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
翻译
许多蛋白质的激活机制的详细信息是个谜。蛋白质的机制和功能是系统结构和动力学的产物。动力学行为对于标准结构研究(如X射线晶体学和CryoEM)是不可见的。为了提高我们对蛋白质药物靶标如何响应配体的理解,需要开发可以探测动力学的方法。氢氘交换质谱(HDX-MS)是一种广泛使用的实验技术,其提供关于蛋白质的酰胺氢键网络的定量信息,从而促进蛋白质构象动力学的探索。HDX-MS在其他互补生物物理技术中脱颖而出,因为它比许多其他方法具有优势,因为它可以研究的蛋白质大小没有限制,并且可以在类似于天然环境的条件下探测蛋白质。因此,HDX-MS广泛用于小分子、抗体和疫苗应用。在小分子研究中,HDX-MS可以报告直接结合事件和变构调节。在构象机制的研究中,通过限制蛋白质的构象状态,可以绕过HDX数据到结构表征的完全去卷积。这类实验研究通常由分子动力学(MD)模拟补充,可用于监测蛋白质及其复合物的构象动力学。HDX-MS在抗体治疗研究中的频繁使用强调了其作为分析科学常规使用的分支的地位。实验方法结合了生物信息学和计算与理论化学。HDX-MS涉及将蛋白质分解为肽,然后必须匹配肽片段/蛋白质序列,由于不同肽/质量可能性的数量,这可能具有挑战性。因此,MD模拟用于帮助解决由此产生的数据中的差距,并帮助将空间分布的汇率结构功能。由于蛋白质本质上是非线性系统,因此MD模拟需要仔细实施以将动态观察重新加权到模拟结构,将动态与蛋白质功能联系起来。目前,存在两种主要制度进行HDX-MS研究:丰富的实验和模拟丰富。一个主要的研究目标是比较这两种方法,并应用HDX-MS以及MD模拟的最新技术。这一目标将通过团队的跨学科经验相结合来实现:实验HDX-MS(Srinath Krishnamurthy,OMass),计算化学(Maria Musgaard,OMass),HDX-MS的理论方法(奥利弗克鲁克,牛津)和结构生物学和统计学(夏洛特迪恩,牛津)。在这个项目中,我们将开发HDX-MS和MD之间的整合方法,以研究多种小分子调节剂激活受体的机制。除了简单地对比最佳实践,我们计划探索的一个有趣的领域是这些数据的图形和可视化,固有的高维性可能会使解释具有挑战性。来自已发表研究的大量HDX-MS数据可用,并提供了比较不同方法的测试平台。此外,OMass目前有几项研究可供探索,并有可能通过进一步的实验来补充数据。这将使我们能够研究HDX-MS实验的最新进展。最初,我们将利用在先前的工作中通过HDX-MS(通过HDX-MS研究的38种化合物和大约60个PDB结构)从ROR γ调节剂的结构动力学库中产生的大量数据来确定是否可以预测或从试图揭示激活的构象动力学的MD轨迹中选择正确的蛋白质-配体复合物构象。
英文摘要
Detailed information on the mechanism of activation is enigmatic for many proteins. Protein mechanism and function is a product of both the structure and the dynamics of the system. Dynamical behaviour is invisible to standard structural studies such as X-ray crystallography and CryoEM. To improve our understanding of how protein drug targets respond to ligands requirements the development of methods that can probe dynamics. Hydrogen-Deuterium Exchange Mass-Spectrometry (HDX-MS) is a widely used experimental technique that provides quantitative information on the protein's amide hydrogen bonding network, thereby facilitating the exploration of protein conformational dynamics. HDX-MS stands out to other complementary biophysical techniques as it has advantages over many other methods in that there is no limit to the size of protein it can study and it can probe proteins in conditions similar to the native environment. As such HDX-MS is extensively used in small molecule, antibody, and vaccine applications. In small molecule research, HDX-MS can report on both direct binding events and allosteric modulation. In studies of conformational mechanism, the full deconvolution of HDX data into structural representation can be bypassed by restricting the conformational state of proteins. These sorts of experimental studies are often complemented by Molecular Dynamics (MD) simulations that can be used to monitor the conformational dynamics of proteins and their complexes. The frequent use of HDX-MS in antibody therapeutics research underscores its position as a routinely utilized branch of Analytical Science. The experimental method combines Biological Informatics and Computational and Theoretical Chemistry. HDX-MS involves breaking down a protein into peptides, the peptide fragment/protein sequences must then be matched which can be challenging due to the number of different peptide/mass possibilities. MD simulations are therefore used to help resolve gaps in the resulting data and to help relate the spatially distributed exchange rates to structural functions. As proteins are inherently Non-Linear Systems, the MD simulations require careful implementation to reweight the dynamical observations to simulated structures, to link dynamics to protein function. Presently, two main regimes exist for performing HDX-MS studies: experiment rich and simulation rich. A primary research objective is to compare the two approaches and apply the latest techniques from both HDX-MS as well as MD simulation. This goal will be achieved by the combination interdisciplinary experience of the team: experimental HDX-MS (Srinath Krishnamurthy, OMass), computational chemistry (Maria Musgaard, OMass), theoretical methods in HDX-MS (Oliver Crook, Oxford) and structural biology and statistics (Charlotte Deane, Oxford). In this project, we will develop an integrative approach between HDX-MS and MD to investigate the mechanism of activation of receptors with multiple small molecule modulators. Beyond simply contrasting best practices, one intriguing area we plan to explore is the Graphics and Visualisation of these data, the inherent high dimensionality can make interpretation challenging. A wealth of HDX-MS data from published studies are available and provide a testbed to compare different approaches. In addition, OMass has several current studies for exploration as well as the possibility to supplement the data with further experiments. This will enable us to investigate the latest advancements in HDX-MS experiments. Initially we will leverage the wealth of data generated in previous work on a library of structural dynamics from RORy modulators by HDX-MS (38 compounds studied via HDX-MS and around 60 pdb structures) to determine whether the correct protein-ligand complex conformations can be predicted or selected from MD trajectories attempting to reveal the conformational dynamics of activation.
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