Mapping Fitness and Free Energy Landscapes of Proteins

项目摘要 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.蛋白质复杂构象和适合度图谱 构象动力学在分子识别和统计调控中起着重要的作用 力学提供了一个框架，以获得一个全面的理论结合自由能的配体， 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，以预测热力学和 动力学性质，但同样重要的是，产生定性的见解的分子机制， 结合和变构构象转变。强大的反向推理统计方法正在被 开发用于研究蛋白质序列共变异和蛋白质适合度之间的关系。该公司- 蛋白质家族的多重序列比对中包含的突变对的变异将用于 建立序列模式的Potts Hamilton模型，可用于预测适应度的变化 以及推断个体构象倾向的特征 proteins. 2.激酶选择性的结构基础和小分子调控 人类激酶组编码约518种激酶（PKs），其构成最大类基因之一。 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 生物学我们与福克斯蔡斯癌症中心和哥伦比亚大学的合作者一起， 生物物理模拟和进化序列为基础的方法，以合理化生化分析 激酶的研究，并设计一个框架，了解选择性的分子机制， 激酶抑制剂的作用。 3. HIV-1蛋白的抑制与耐药机制 我与科罗拉多大学、哈佛大学和斯克里普斯大学的研究小组合作， HIV-1蛋白小分子抑制的基础，耐药性机制，以及 HIV蛋白质在不同HIV进化枝中适合度的比较研究。变构HIV-1 IN抑制剂称为 ALLINI是一类重要的新型抗HIV-1药物。ALLINI结合IN催化核心结构域（CCD） 二聚体界面占据LEDGF的主要结合口袋。利用构象自由能 模拟工具和基于序列的工具，我们正在开发，以了解相关的突变，我们是 与我们的合作者一起确定ALLINI的抑制机制，以及药物治疗的基础。 阻力

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.