Quantitative, Mechanistic Studies of Biomolecular Recognition

生物分子识别的定量、机制研究

• 批准号: 9071084
• 负责人: Huan-Xiang Zhou
• 金额: $ 19.92万
• 依托单位: FLORIDA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-15 至 2021-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9071084
• 关键词: Affect; Allosteric Regulation; Binding; Binding Proteins; Biology; Crowding; Disease; Drug Design; Environment; Exclusion; Experimental Designs; Goals; Knowledge; Liquid substance; Measurement; Molecular; Motion; Pathway interactions; Process; Property; Proteins; Regulation; Research; Signal Transduction; Testing; Theoretical model; Thermodynamics; base; cellular targeting; macromolecule; molecular recognition; physical property; public health relevance; response; simulation

 DESCRIPTION (provided by applicant): Biomolecular research is increasingly changing from phenomenological and descriptive to quantitative and predictive. The overall goal of the proposed research is to facilitate this paradigm shift in mechanistic studies of biomolecular recognition, which occurs at a wide range of spatial scales. Protein-ligand binding and allosteric regulation are the prototypical molecular recognition processes. Moving up the spatial scale, many intrinsically disordered proteins have now been identified, often involved in signaling or regulation by binding to their cellular targets. At the subcellular scale, exciting discoveries are being made about a membraneless form of micro-compartments, wherein specific proteins and RNAs are condensed but remain fluid. These "intracellular bodies" assemble reversibly in response to regulatory signals and can recognize "bystander" components for exclusion. High concentrations of bystander macromolecules ("crowders") are always present in the cellular environments and affect all these molecular recognition processes. Irrespective of spatial scales, the fundamental basis of molecular recognition is the molecular physical properties, including molecular interactions and motions. To gain deep mechanistic knowledge on all these molecular recognition processes, the proposed research will use three complementary approaches. Theoretical models will be developed to test mechanistic hypotheses and guide experimental design and to establish the framework for relating thermodynamic and mechanistic properties to molecular physical properties. The framework will be implemented computationally, through molecular simulations and atomistic-level calculations. Experimental measurements will be made to obtain critical information, which will also serve to inspire theoretical models and validate computational results. Through the integration of the three approaches, the effects of macromolecular crowding will be characterized, such that the knowledge from dilute-solution studies can be transferred to the cellular context. The deep, quantitative understanding of biomolecular recognition to be achieved will enable accurate predictions of mechanistic properties and yield opportunities for drug design through altering mechanistic pathways.

 描述（申请人提供）：生物分子研究正日益从现象学和描述性的定量和预测。拟议的研究的总体目标是促进这种范式转变的机制研究的生物分子识别，这发生在广泛的空间尺度。蛋白质-配体结合和变构调节是典型的分子识别过程。在空间尺度上，许多内在无序的蛋白质现在已经被鉴定出来，它们通常通过与细胞靶点结合来参与信号传导或调节。在亚细胞尺度上，令人兴奋的发现是 由无膜形式的微区室制成，其中特定的蛋白质和RNA被浓缩但保持流体。这些“细胞内体”响应于调节信号可逆地组装，并且可以识别“旁观者”组分以进行排除。高浓度的旁观者大分子（“拥挤者”）总是存在于细胞环境中，并影响所有这些分子识别过程。无论空间尺度如何，分子识别的基本基础是分子的物理性质，包括分子间的相互作用和运动。为了深入了解所有这些分子识别过程的机理，拟议的研究将使用三种互补的方法。理论模型将被开发来测试机制假设和指导实验设计，并建立相关的热力学和机械性能的分子物理性质的框架。该框架将通过分子模拟和原子级计算在计算上实现。将进行实验测量，以获得关键信息，这也将有助于启发理论模型和验证计算结果。通过这三种方法的整合，大分子拥挤的影响将被表征，从而可以将来自稀溶液研究的知识转移到细胞环境中。要实现的生物分子识别的深入，定量的理解将能够准确预测的机械性能和产量的机会，通过改变机械途径的药物设计。