Understanding protein folding, evolution and function via molecular simulation

通过分子模拟了解蛋白质折叠、进化和功能

• 批准号: 10699679
• 负责人: Robert Best
• 金额: $ 67.37万
• 依托单位: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10699679
• 关键词: 2019-nCoV; Address; Affinity; Aging; Amino Acid Sequence; Amyloid; Area; Back; Base Sequence; Cell Nucleus; Charge; Collaborations; Collagen; Collagen Fiber; Complex; Cytoplasmic Granules; DNA; Data; Data Set; Development; Disease; Energy Transfer; Evolution; Extracellular Matrix; Fluorescence Resonance Energy Transfer; Goals; Grain; Histones; Investigation; Ions; Liquid substance; Machine Learning; Measurement; Membrane Proteins; Methodology; Methods; Modeling; Molecular; Molecular Chaperones; Molecular Structure; Nuclear Proteins; Nucleic Acids; Nucleosomes; Organelles; Osmotic Pressure; Peptide Hydrolases; Peptides; Phase; Process; Property; Protein Engineering; Proteins; RNA; Refit; Resolution; Roentgen Rays; Route; Set protein; Sodium Chloride; Source; Speed; Spin Labels; Structure; Supervision; Testing; Time; Work; amyloid fibril formation; density; design; experimental study; fitness; improved; interest; macromolecule; member; models and simulation; novel; predictive modeling; protein aggregation; protein complex; protein folding; protein function; protein misfolding; simulation; single-molecule FRET; theories; thermostability

The project has addressed the following areas in the past year: 1. Association of highly charged intrinsically disordered proteins and their complex coacervation. Recent work in collaboration with Ben Schuler's single molecule FRET group in Zurich has shown that high affinity disordered complexes of proteins or proteins and nucleic acids of opposite charge may be ubiquitous in cell nuclei. We have previously shown that this mode of association allows a competitive substitution mechanism that speeds unbinding, e.g. allowing protein chaperones to release histones from nucleosome complexes (1). We are now seeking to develop a predictive model for the affinity and structure of these complexes, informed by molecular simulations of a variety of sequences, as well as experimental data. Using novel multiscale simulation methodology, are also performing all-atom simulations of a complex coacervate of two nuclear proteins in order to elucidate the interactions responsible for stabilizing these phases, and we are also using new experimental data from FRET experiments and osmotic pressure measurements to help refine the force fields for salt bridges in the proteins as well as interactions of the proteins with ions (M. Ivanovic). 2. Development of coarse-grained models for complex coacervation of intrinsically disordered proteins with single- and double-stranded nucleic acids. Going beyond the 1:1 complexes studied in project 1, it is also possible for oppositely charged macromolecules such as proteins and DNA or RNA to undergo complex coacervation, forming a separate phase with high macromolecular density, under the correct conditions. Such a phenomenon may provide a physical basis for the formation of some of the membraneless organelles observed in the cell nucleus. We have developed a coarse-grained simulation model of protein-nucleic acid interactions, and used it to study the ordering induced on formation of the condensed phase. We are currently extending this model to include sequence-specific effects as well as back-mapping to atomistic simulations in a multiscale approach (3). (K. Lebold) 3. Development of transferable sequence-specific models for liquid-liquid phase separation (LLPS) of intrinsically disordered proteins. We had previously shown that a comprehensive refitting of the parameters of our coarse-grained the energy function for proteins was able to better describe the both the properties of isolated disordered chains and also those of proteins which are known to phase separate; however that work relied on data from disparate sources and collected under different conditions. We have now used a FRET data set on a set of proteins with diverse sequences collected under identical conditions in the Schuler lab to further refine the potential, resulting in significant improvements. We are also extending this model to capture specific structure formation (e.g. amyloid) to model possible aging processes in droplets and developing models for cosolvent and Hofmeister effects which are sometimes of interest experimentally. (T. Dannenhoffer-Lafage) 4. Using sequence-based energy functions to describe protein fitness landscapes and for protein design. We have shown that it is possible to design novel foldable protein sequences using coevolutionary models. Most recently we have found that we can achieve increased thermostability via this route. We are also seeking to design sequences which can fold into two different structures as envisaged in our recent theoretical work, and we are collaborating with Susan Marqusee's group to test some of these ideas (P. Tian). We are also looking to develop similar ideas to identify proteins which naturally switch folds (such as RfaH), using sequence information. Separately, we are exploring the use of machine learning to predict fitness landscapes for proteins of any given structure (L. Frechette, D. Wang). 5. Modelling properties of the extracellular matrix using coarse-grained models. We have recently started developing bottom up coarse-grained simulation models to describe the extracellular matrix and how they are related to its underlying molecular structure. We have initially focused on developing accurate atomistic models for collagen, and validating them against the available data from NMR and small angle X-ray scattering; we are extending this to coarse-grained models that will allow the investigation of packing of tropocollagen in collagen fibers. (G. Pantelopulos). 6. Inferring interactions between proteins and cosolutes using NMR data. In collaboration with Yusuke Okuno and Marius Clore, we have been using simulations in conjunction with experiments to analyze association of denaturant molecules with proteins using spin-labelled denaturants. For the first time we have shown directly that the denaturant mechanism involves primarily interactions with the unfolded state. We are now extending this work and developing all-atom models for the spin-labelled cosolutes (T. Dannenhoffer-Lafage). 7. We are working in collaboration with Steve Vogel to understand the mechanisms in certain fluorescent proteins that allow coherent energy transfer via models parameterized from molecular simulations. (G. Taumoefolau). Group members or jointly supervised external collaborators involved in each project are listed at the end of each section.

该项目在过去一年中处理了以下领域： 1.高电荷内在无序蛋白质的缔合及其复合凝聚。最近与苏黎世的Ben舒勒的单分子FRET组合作的工作表明，蛋白质或蛋白质与相反电荷的核酸的高亲和力无序复合物可能在细胞核中普遍存在。我们之前已经表明，这种缔合模式允许竞争性取代机制，加速解结合，例如允许蛋白质伴侣从核小体复合物中释放组蛋白（1）。我们现在正在寻求开发一个预测模型的亲和力和这些复合物的结构，通过分子模拟的各种序列，以及实验数据。使用新的多尺度模拟方法，还进行了两个核蛋白质的复杂凝聚层的全原子模拟，以阐明负责稳定这些相的相互作用，我们还使用FRET实验和渗透压测量的新实验数据来帮助改进蛋白质中盐桥的力场以及蛋白质与离子的相互作用（M。伊万诺维奇）。 2.本征无序蛋白质与单链和双链核酸复合凝聚的粗粒模型的发展。除了项目1中研究的1：1复合物之外，在正确的条件下，带相反电荷的大分子（如蛋白质和DNA或RNA）也可以进行复合凝聚，形成具有高大分子密度的分离相。这种现象可能为在细胞核中观察到的一些无膜细胞器的形成提供了物理基础。我们建立了一个蛋白质-核酸相互作用的粗粒度模拟模型，并利用它来研究凝聚相形成过程中的有序性。我们目前正在扩展该模型，以包括序列特异性效应以及多尺度方法中的原子模拟的反向映射（3）。（K. Lebold） 3.开发用于本质无序蛋白质液-液相分离（LLPS）的可转移序列特定模型。我们之前已经表明，对我们粗粒度蛋白质能量函数的参数进行全面改装能够更好地描述孤立无序链的性质以及已知相分离的蛋白质的性质;然而，这项工作依赖于来自不同来源的数据，并在不同条件下收集。我们现在使用了在舒勒实验室相同条件下收集的一组具有不同序列的蛋白质的FRET数据集来进一步细化潜力，从而取得了显着的改进。我们还扩展了这个模型，以捕获特定的结构形成（例如淀粉样蛋白），以模拟液滴中可能的老化过程，并开发了共溶剂和Hofmeister效应的模型，这些模型有时在实验上很有趣。（T.（Dannenhoffer-Lafage） 4.使用基于序列的能量函数来描述蛋白质适应度景观和蛋白质设计。我们已经表明，它是可能的设计新的折叠蛋白质序列使用共同进化模型。最近，我们发现我们可以通过这种途径实现增加的热稳定性。我们还在寻求设计可以折叠成两种不同结构的序列，正如我们最近的理论工作所设想的那样，我们正在与Susan Marqusee的小组合作，以测试其中的一些想法。我们还希望开发类似的想法，利用序列信息来识别自然转换折叠的蛋白质（如RfaH）。另外，我们正在探索使用机器学习来预测任何给定结构的蛋白质的适应度景观。Frechette，D. Wang）。 5.使用粗粒度模型模拟细胞外基质的特性。我们最近开始开发自下而上的粗粒度模拟模型来描述细胞外基质以及它们如何与其底层分子结构相关。我们最初专注于开发胶原蛋白的精确原子模型，并根据NMR和小角X射线散射的可用数据对其进行验证;我们正在将其扩展到粗粒度模型，以便研究胶原蛋白纤维中原胶原蛋白的包装。 （G. Pantelopulos）。 6.利用核磁共振数据推断蛋白质和共溶质之间的相互作用。在与Yusuke Okuno和Marius Clore的合作中，我们一直在使用模拟结合实验来分析变性剂分子与蛋白质的关联，使用自旋标记的变性剂。我们第一次直接表明，变性机制主要涉及与未折叠状态的相互作用。我们现在正在扩展这项工作，并为自旋标记的共溶质（T。Dannenhoffer-Lafage）。 7.我们正在与Steve Vogel合作，以了解某些荧光蛋白的机制，这些荧光蛋白允许通过分子模拟参数化的模型进行相干能量转移。（G. Taumoefolau）。 参与每个项目的小组成员或共同监督的外部合作者列在每个部分的末尾。