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.

项目摘要 我们的长期目标是整合基于统计力学的基于结构和序列的方法 了解蛋白质分子识别的关键特征，以及蛋白质适应性和功能更多 一般来说。 1。映射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本作用 力学提供了一个框架，以得出配体与配体的结合自由能的综合理论 蛋白质。我们的目标是使用基于分子动力学模拟的高级抽样方法 构建足够精度的构象自由能景观，以预测热力学和 动力学特性，但同样重要，以产生有关分子机制的定性见解 结合和变构构象过渡。强大的反推理统计方法正在 开发用于研究蛋白质序列共同变化与蛋白质适应性之间的关系。共同 蛋白质家族多个序列比对中包含的突变对的变化将用于 构建可用于预测健身变化的序列模式的potts Hamiltonian模型 由药物选择压力以及个体构象倾向的特征引起的 蛋白质。 2。小分子的激酶选择性和调节的结构基础 人类动物组编码约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一个概念框架 生物学。与我们在Fox Chase Cancer Center和Columbia University的合作者一起，我们正在研究 生物物理模拟和基于进化序列的方法，以合理化生化分析 激酶的研究并设计一个框架来理解选择性的分子机制 激酶抑制剂对其靶标。 3。抑制HIV-1蛋白和耐药性机制 我与科罗拉多大学，哈佛大学和斯克里普斯的小组合作，我正在研究变构 小分子对HIV-1蛋白的抑制作用，耐药性机理以及 HIV蛋白在不同HIV进化枝中适应性的比较研究。抑制剂中的变构HIV-1称为 Allinis是一类新的抗HIV-1代理。 Allinis在催化核心结构域（CCD）上结合 LEDGF的主绑定袋中的二聚体界面。使用我们的构象自由能 模拟工具和我们正在开发的基于序列的工具以了解相关突变，我们是 与我们的合作者合作，以确定Allinis的抑制性机甲和毒品的基础 反抗。