Mapping Fitness and Free Energy Landscapes of Proteins

项目摘要 我们的长期目标是整合建立在统计力学基础上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，以及蛋白质的适合性和功能 一般说来。 1.绘制蛋白质的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基础性的作用 力学提供了一个框架来推导配体的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来 构造足够精确的构象自由能景观以预测热力学和 动力学性质，但也同样重要，以产生对分子机制的定性见解 结合构象和变构构象转变。强大的逆推理统计方法正在成为 研究蛋白质序列协变与蛋白质适合度之间的关系。联席- 蛋白质家族的多个序列比对中包含的突变对的变异将用于 建立可用于预测适应度变化的序列模式的Potts哈密顿模型 由药物选择压力产生，以及推断个体构象倾向的特征 蛋白质。 2.酶选择性的结构基础及小分子调控 人类近亲基因组编码大约518个蛋白激酶(PKs)，它们构成了最大的一类基因。 蛋白激酶结构生物学的进展为理解蛋白激酶的许多方面提供了一个概念性框架 生物学。与我们在福克斯·蔡斯癌症中心和哥伦比亚大学的合作者一起，我们正在 基于生物物理模拟和进化序列的生化图谱合理化方法 研究肌动蛋白，并设计一个框架，以了解选择性的分子机制 对它们的靶标有抑制作用。 3.抑制HIV-1蛋白与耐药机制 与科罗拉多大学、哈佛大学和斯克里普斯大学的团队合作，我正在研究变构 HIV-1蛋白小分子抑制的基础，耐药机制，以及 不同HIV分支中HIV蛋白适合性的比较研究。变构HIV-1抑制剂称为 ALLINI是一类重要的新型抗HIV-1药物。大蒜素结合在IN催化核心区(CD) 二聚体界面占据LEDGF的主结合口袋。利用我们的构象自由能 我们正在开发的模拟工具和基于序列的工具来了解相关的突变，我们是 与我们的合作者合作，以确定Allini的抑制机制，以及药物的基础 抵抗。

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.