Mapping Fitness and Free Energy Landscapes of Proteins

绘制蛋白质的健康度和自由能景观

• 批准号: 10402303
• 负责人: Ronald Levy
• 金额: $ 37.13万
• 依托单位: TEMPLE UNIV OF THE COMMONWEALTH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10402303
• 关键词: Amino Acid Sequence; Base Sequence; Binding; Biochemical; Biology; Biophysics; Catalytic Domain; Collaborations; Colorado; Comparative Study; Complex; Data; Drug resistance; Fox Chase Cancer Center; Free Energy; Genes; Goals; HIV; HIV-1; Human; Individual; Kinetics; Ligands; Methods; Modeling; Molecular; Molecular Conformation; Mutation; Pattern; Pharmaceutical Preparations; Phosphotransferases; Play; Property; Protein Conformation; Protein Family; Proteins; Regulation; Role; Sampling; Sequence Alignment; Statistical Mechanics; Structure; Thermodynamics; Universities; Variant; base; conformational conversion; design; dimer; fitness; inhibitor; insight; kinase inhibitor; molecular dynamics; molecular recognition; pressure; resistance mutation; simulation; small molecule; structural biology; theories; tool

Project Summary Our long term goal is to integrate structure and sequence based approaches founded in statistical mechanics to understand key features of molecular recognition by proteins, as well as protein fitness and function more generally. 1. Mapping Complex Conformational and Fitness Landscapes of Proteins Conformational dynamics plays a fundamental role in the regulation of molecular recognition and statistical mechanics provides the framework to derive a comprehensive theory for the binding free energy of a ligand to a protein. Our goal is to use advanced sampling methods based on molecular dynamics simulations to construct conformational free energy landscapes of sufficient accuracy to be predictive for thermodynamic and kinetic properties, but also as important, to generate qualitative insights about the molecular mechanisms for binding and allosteric conformational transitions. Powerful inverse inference statistical approaches are being developed to study the relationship between protein sequence co-variation and protein fitness. The co- variation of pairs of mutations contained in multiple sequence alignments of protein families will be used to build Potts Hamiltonian models of the sequence patterns that can be used to predict the change in fitness resulting from drug selection pressure, as well as infer features of the conformational propensities of individual proteins. 2. The Structural Basis for Kinase Selectivity and Regulation by Small Molecules The human kinome encodes about 518 kinases (PKs) which constitute one of the largest class of genes. Progress in kinase structural biology offers a conceptual framework for understanding many aspects of kinase biology. With our collaborators at the Fox Chase Cancer Center and Columbia University we are working on biophysical simulation and evolutionary sequence based approaches to rationalize biochemical profiling studies of kinases and to devise a framework for understanding the molecular mechanisms of selectivity of kinase inhibitors to their targets. 3. Inhibition of HIV-1 Proteins and Mechanisms of Drug Resistance In collaboration with groups at the University of Colorado, Harvard and Scripps, I am working on the allosteric basis for inhibition by small molecules of HIV-1 proteins, on mechanisms of drug resistance, and on comparative studies of the fitness of HIV proteins in different HIV clades. Allosteric HIV-1 IN inhibitors called ALLINIs are an important new class of anti-HIV-1 agents. ALLINIs bind at the IN catalytic core domain (CCD) dimer interface occupying the principal binding pocket of LEDGF. Using our conformational free energy simulation tools and the sequence based tools we are developing to understand correlated mutations, we are working with our collaborators to ascertain the inhibitory mechansims of ALLINIs, and the basis for drug resistance.

项目概要 我们的长期目标是整合基于统计力学的结构和序列方法 了解蛋白质分子识别的关键特征，以及蛋白质的适应性和功能 一般来说。 1. 绘制蛋白质的复杂构象和健身景观 构象动力学在分子识别和统计的调节中起着基础作用 力学提供了一个框架来导出配体结合自由能的综合理论 一种蛋白质。我们的目标是使用基于分子动力学模拟的先进采样方法 构建足够准确的构象自由能景观来预测热力学和 动力学特性，但也同样重要的是，产生关于分子机制的定性见解 结合和变构构象转变。强大的逆推统计方法正在被开发 开发用于研究蛋白质序列共变和蛋白质适应性之间的关系。该共同 蛋白质家族的多重序列比对中包含的突变对的变异将被用于 构建序列模式的 Potts Hamiltonian 模型，可用于预测适应度的变化 由药物选择压力产生的结果，以及推断个体构象倾向的特征 蛋白质。 2. 小分子激酶选择性和调节的结构基础 人类激酶组编码约 518 个激酶 (PK)，构成最大的基因类别之一。 激酶结构生物学的进展为理解激酶的许多方面提供了概念框架 生物学。我们正在与福克斯蔡斯癌症中心和哥伦比亚大学的合作者一起努力 基于生物物理模拟和进化序列的方法来合理化生化分析 激酶的研究并设计一个框架来理解激酶选择性的分子机制 激酶抑制剂针对其靶点。 3. HIV-1蛋白的抑制和耐药机制 我正在与科罗拉多大学、哈佛大学和斯克里普斯大学的研究小组合作，研究变构 HIV-1 蛋白小分子抑制、耐药机制以及 不同HIV分支中HIV蛋白的适应性的比较研究。 HIV-1 IN 变构抑制剂称为 ALLINI 是一类重要的新型抗 HIV-1 药物。 ALLINI 结合于 IN 催化核心结构域 (CCD) 二聚体界面占据 LEDGF 的主要结合袋。利用我们的构象自由能 我们正在开发模拟工具和基于序列的工具来理解相关突变，我们正在 与我们的合作者合作，确定 ALLINI 的抑制机制以及药物的基础 反抗。