Predicting protein flexibility and stability

预测蛋白质的灵活性和稳定性

• 批准号: 7269710
• 负责人: Donald JACOBS
• 金额: $ 4.63万
• 依托单位: UNIVERSITY OF NORTH CAROLINA CHARLOTTE
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-03-01 至 2010-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7269710
• 关键词: Predicting; protein; flexibility; stability

DESCRIPTION (provided by applicant): A grand challenge of biophysics is to understand protein folding, stability, flexibility, and function in terms of structure and solvent condition. A novel Distance Constraint Model (DCM) is employed to accurately predict protein stability in aqueous solution under specified thermodynamic conditions (i.e. temperature, pH, ionic strength, etc) from known three-dimensional structure. This project builds upon prior success of the PI in developing efficient rigidity-graph algorithms to identify flexible and rigid regions in proteins modeled as a fixed constraint topology, and development of the DCM. The DCM is based on the hypothesis that network rigidity is an underlying mechanism for enthalpy-entropy compensation, yielding a mathematically precise algorithm to account for non-additivity in free energy decompositions. A proof of concept, minimal DCM, will be extended in this project to include explictit modeling of essential entropy-compensation mechanisms that include (a) hydration, (b) hydrophobic interactions, (c) electrostatics interactions, with (d) a residue-specific parameterization. These extensions will allow prediction of protein stability in mixed solvent conditions, and bring the DCM closer to a fully transferable parameterization. However, parameter transferability is not a requirement of this proposed work, as the utility of our minimal DCM has been firmly established. The first outcome of this work will be the release of a fast computational tool that harmoniously quantifies stability and flexibility in practical computing times necessary for protien design applications. For example, local- details of protein flexibility are quantified to identify correlated atomic motions important for induced fit of ligand binding and allosteric conformational changes. Synergistic application of the DCM with protein family evolutionary descriptions will provide key insight into familial variability of Quantified Stability/Flexibility Relationships (QSFR). The second outcome will be a public accessible QSFR database providing users wide access to DCM results and analysis tools will give users a practical means to better understand protein function in realistic computing times needed for the post-geonomic era.

描述（由申请人提供）：生物物理学的一大挑战是了解蛋白质折叠、稳定性、灵活性以及结构和溶剂条件方面的功能。采用一种新颖的距离约束模型 (DCM)，根据已知的三维结构准确预测特定热力学条件（即温度、pH、离子强度等）下水溶液中蛋白质的稳定性。该项目建立在 PI 先前成功开发高效刚性图算法以识别建模为固定约束拓扑的蛋白质中的柔性和刚性区域以及 DCM 开发的基础上。 DCM 基于这样的假设：网络刚性是熵补偿的基本机制，从而产生数学上精确的算法来解释自由能分解中的非可加性。概念证明，最小 DCM，将在该项目中扩展，以包括基本熵补偿机制的显式建模，其中包括（a）水合，（b）疏水相互作用，（c）静电相互作用，以及（d）残基-具体参数化。这些扩展将允许预测混合溶剂条件下的蛋白质稳定性，并使 DCM 更接近完全可转移的参数化。然而，参数可传递性并不是这项拟议工作的要求，因为我们的最小 DCM 的实用性已经得到了牢固的确立。这项工作的第一个成果将是发布一种快速计算工具，该工具可以和谐地量化蛋白质设计应用所需的实际计算时间的稳定性和灵活性。例如，对蛋白质灵活性的局部细节进行量化，以识别对于配体结合和变构构象变化的诱导拟合很重要的相关原子运动。 DCM 与蛋白质家族进化描述的协同应用将为量化稳定性/灵活性关系 (QSFR) 的家族变异性提供重要见解。第二个成果将是一个公共可访问的 QSFR 数据库，为用户提供广泛的 DCM 结果访问，分析工具将为用户提供一种实用的方法，以便在后基因组时代所需的实际计算时间内更好地了解蛋白质功能。