Predicting protein flexibility and stability

预测蛋白质的灵活性和稳定性

• 批准号: 7028046
• 负责人: Donald JACOBS
• 金额: $ 37.86万
• 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/7028046
• 关键词: biophysics; computational biology; conformation; gene mutation; hydrogen bond; hydropathy; ionic bond; model design /development; molecular biology information system; protein folding; protein structure function; thermodynamics; thermostability; water solution

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）：生物物理学的巨大挑战是了解蛋白质折叠，稳定性，灵活性和功能，并在结构和溶剂状态方面。使用已知的三维结构中的指定热力学条件（即温度，pH，离子强度等），采用了一种新型的距离约束模型（DCM）来准确预测水溶液中的蛋白质稳定性。该项目基于PI在开发有效的刚性图形算法方面的先前成功，以确定模型为固定约束拓扑的蛋白质中的柔性和刚性区域，以及DCM的开发。 DCM基于以下假设：网络刚度是焓 - 熵补偿的基本机制，从而得出了一种数学上精确的算法，以说明自由能分解中的非差异。该项目将扩展概念证明，最小的DCM，包括对必需熵补偿机制的解释建模，其中包括（a）水合，（b）疏水相互作用，（c）静电相互作用，以及（d）残基特异性参数化。这些扩展将允许在混合溶剂条件下预测蛋白质稳定性，并使DCM更接近完全可转移的参数化。但是，参数可传递性并不是这项拟议工作的要求，因为我们最小的DCM的效用已经牢固地确定。这项工作的第一个结果将是发布快速计算工具，该工具可以和谐地量化蛋白设计应用所需的实用计算时间的稳定性和灵活性。例如，量化了蛋白质灵活性的局部细节，以识别与配体结合和变构构象变化诱导拟合至关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）的家族变异性提供关键的见解。第二个结果将是一个公共访问的QSFR数据库，可为用户提供广泛访问DCM结果和分析工具，并为用户提供一种实用手段，以更好地理解后者时代所需的实际计算时间蛋白质功能。