Soft Matter Simulation and Theory of the Crystal Assembly of Globular and Membrane Proteins

球状和膜蛋白晶体组装的软物质模拟和理论

基本信息

批准号：
1749374
负责人：
Patrick Charbonneau
金额：
$ 27万
依托单位：
Duke University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-04-15 至 2022-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1749374&HistoricalAwards=false
关键词：
Soft Matter Simulation Theory Crystal

项目摘要

NONTECHNICAL SUMMARYDivision of Materials Research and the Chemistry Division contribute funds to this award. This award supports theoretical and computational research and education into the crystallization of proteins, which are molecules that are essential to all life forms. Protein crystallization is a key step in determining their structure. Knowing the structure of a protein, in turn, is crucial for understanding its role in biology. Proteins indeed interact with each other and their environment through fine-tuned features. Limited knowledge of protein structures hinders the comprehension of biological molecules and the ability to discover new drugs that interacts with them. The research team will identify how weak yet directional interactions lead to the complex processes through which certain classes of proteins can form crystals. It will also study the materials properties of the ordered lipid phases used for crystallizing those proteins that reside within the membrane of cells.The award also supports the education of students at Duke University, and the PI's participation in various outreach activities within the state of North Carolina and nationally. Through close collaboration with experimental scientists, the findings of the research team will also be tested and used by the protein crystallization community. As a complement to this work, the PI will lead a joint industry-academia consortium aiming to automatize image analysis of protein crystallization experiments, which should dramatically accelerate the experimental process and data gathering. TECHNICAL SUMMARYDivision of Materials Research and the Chemistry Division contribute funds to this award. This award supports theoretical and computational research and education on the soft matter theory and computational modeling of the crystallization of globular proteins and of the lipidic assemblies central to in-meso crystallization of membrane proteins. Both processes are key for protein-structure determination through crystallographic techniques yet are challenging to control experimentally and thus could benefit from additional insight from physical models. More specifically, the research team will examine how weak, non-covalent yet directional interactions lead to the complex crystallization behavior of different classes of proteins. They will study the crystallization of globular proteins that: (i) dimerize, (ii) display an inverted solubility, and (iii) are composed of multiple subdomains. All three cases fall beyond the canonical description of protein crystal assembly. By developing theoretical and computational soft matter models that capture the essence of these richer types of protein crystal assembly, the research team will guide parallel experimental efforts by collaborating researchers.The research team will also examine the formation of lipidic mesophases, which are commonly used for the in-meso crystallization process of membrane proteins but whose microscopic role is incompletely understood. The project will use state-of-the-art numerical tools for determining the phase behavior of various lipid models and examine how membrane proteins embed and order within these ordered phases.The award also supports the education of students at Duke University, and the PI's participation in various outreach activities. Through close collaboration with experimental researchers in the field of protein crystallization, the findings of the research team will also be tested and broadly implemented. As a complement to this work, the PI will also lead a joint industry-academia consortium aiming to automatize image analysis of protein crystallization experiments, and thus remove the biggest bottleneck in the systematic analysis of these experiments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

材料研究和化学部的非技术摘要为该奖项贡献了资金。该奖项支持蛋白质结晶的理论和计算研究和教育，这些分子对所有生命形式都是必不可少的。蛋白质结晶是确定其结构的关键步骤。进而了解蛋白质的结构对于理解其在生物学中的作用至关重要。蛋白质确实通过微调特征相互互动及其环境。对蛋白质结构的有限了解阻碍了生物分子的理解以及发现与它们相互作用的新药的能力。研究团队将确定弱但方向的相互作用如何导致某些类别的蛋白质可以形成晶体的复杂过程。它还将研究用于结晶细胞膜中那些蛋白质的有序脂质阶段的材料特性。该奖项还支持杜克大学的学生教育，以及PI在北卡罗来纳州和全国范围内参与各种外展活动。通过与实验科学家的密切合作，蛋白质结晶社区还将测试和使用研究团队的发现。作为对这项工作的补充，PI将领导一个联合行业 - 阿卡迪亚联盟，旨在自动化蛋白质结晶实验的图像分析，这应该显着加速实验过程和数据收集。材料研究和化学部的技术摘要为该奖项贡献了资金。该奖项支持有关软物质理论的理论和计算研究和教育，并支持球状蛋白质的结晶和脂质组装的结晶，这是膜蛋白质内结晶中心的脂质组件。这两种过程都是通过晶体学技术确定蛋白质结构的关键，但在实验中控制既有挑战性，因此可以从物理模型的其他见解中受益。更具体地说，研究团队将研究如何导致不同类别蛋白质的复杂结晶行为。他们将研究球状蛋白的结晶：（i）二聚，（ii）显示倒溶解度，（iii）由多个亚域组成。所有三种情况都超出了蛋白质晶体组件的规范描述。通过开发理论和计算软件模型，以捕捉这些较丰富的蛋白质晶体组装的本质，研究团队将指导研究人员合作的平行实验努力。研究团队还将研究脂质中间体的形成，这些脂质中的脂质中的脂质蛋白通常被用于膜蛋白的膜结晶过程，但它们的显微镜蛋白质是无数理解的。该项目将使用最先进的数值工具来确定各种脂质模型的相位行为，并检查膜蛋白如何在这些有序阶段中嵌入和有序。该奖项还支持杜克大学的学生教育，以及PI的参与各种外展活动。通过与蛋白质结晶领域的实验研究人员的密切合作，研究团队的发现也将进行测试和广泛实施。作为对这项工作的补充，PI还将领导一个联合行业 - 阿卡迪亚联盟，旨在自动化蛋白质结晶实验的图像分析，从而消除了对这些实验的系统分析中最大的瓶颈。这奖反映了NSF的法定任务，并通过使用基础的智力效果和广泛的评估来评估支持，并值得评估。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Temperature-Dependent Interactions Explain Normal and Inverted Solubility in a γD-Crystallin Mutant

温度依赖性相互作用解释了γD-晶状体蛋白突变体的正常和反向溶解度

DOI：
10.1016/j.bpj.2019.07.019
发表时间：
2019
期刊：
Biophysical Journal
影响因子：
3.4
作者：
Khan, Amir R.;James, Susan;Quinn, Michelle K.;Altan, Irem;Charbonneau, Patrick;McManus, Jennifer J.
通讯作者：
McManus, Jennifer J.

Tissue self-organization underlies morphogenesis of the notochord

组织自组织是脊索形态发生的基础

DOI：
10.1098/rstb.2017.0320
发表时间：
2018
期刊：
Philosophical Transactions of the Royal Society B: Biological Sciences
影响因子：
0
作者：
Norman, James;Sorrell, Emma L.;Hu, Yi;Siripurapu, Vaishnavi;Garcia, Jamie;Bagwell, Jennifer;Charbonneau, Patrick;Lubkin, Sharon R.;Bagnat, Michel
通讯作者：
Bagnat, Michel

Using Schematic Models to Understand the Microscopic Basis for Inverted Solubility in γD-Crystallin