Improving the Understanding and Application of Multi-Modal Chromatography

提高对多模式色谱的理解和应用

• 批准号: 0933169
• 负责人: Steven Cramer
• 金额: $ 30万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0933169&HistoricalAwards=false
• 关键词: Improving; Understanding; Application; Multi; Modal

0933169CramerThis NSF award by the Chemical and Biological Separations program supports work by Professor Steven Cramer and his colleagues Shekhar Garde and Curt Breneman at Rensselaer Polytechnic Institute to establish a deeper understanding of the nature of selectivity in multi-modal (MM) chromatographic systems. This project will employ a state of the art library of novel multi-modal ligands and materials in concert with protein libraries in a detailed study of MM ligand - protein interactions. The binding of free solution MM ligands to a set of labeled model proteins will be studied using NMR to determine binding kinetics and ligand binding sites on the proteins. Chemical modifications of native proteins will be carried out to generate a diverse set of protein ladders possessing various combinations of surface properties. Chromatographic experiments will be carried out with these proteins along with a set of commercially available proteins under a range of operating conditions to study protein retention behavior and to determine appropriate isotherm models for these MM systems. To complement the experiments, large scale MD simulations of protein-ligand binding in solution, and coarse-grained modeling approaches for protein - multi-modal resin interactions will be carried out. These simulations will provide data on ligand binding sites, modes of binding, and dynamics and thermodynamics of interactions in solution. MD and coarse grained simulations will also provide important data that will be used to generate novel molecular descriptors. Predictive quantitative structure property relationship (QSPR) models of protein affinity and isotherm parameters will be determined using the chromatographic data and novel molecular descriptors. The proposed project will have a significant impact on the development and implementation of MM chromatographic technology for protein purification. This work will facilitate the design of next generation MM chromatographic systems and will provide predictive tools for MM chromatography that will facilitate methods development with these systems for the purification of biotherapeutics. The development of improved MM chromatographic systems will potentially enable a reduction in the number of downstream processing steps required for the purification of therapeutic proteins, reducing the costs of producing biopharmaceuticals. Further, multi-modal separation systems with unique selectivities will provide new novel front end separations for the analysis of proteins by mass spectrometry. Finally, a deeper understanding of the modes of interactions of proteins with various classes of multi-modal ligands and surfaces will have potential implications beyond separations to fields including biomaterials, biosensors, and drug discovery. The proposed research will also have an important impact on the education of both graduate and undergraduate chemical engineering students. The proposed research will be carried out in the Center for Biotechnology and Interdisciplinary Studies which provides excellent multidisciplinary training opportunities for graduate and undergraduate students. Students will gain exposure to cell culture, solution NMR spectroscopy, chromatography, molecular simulations and chemometrics. The research developed in this project will also be incorporated into a chemical engineering senior laboratory chromatography experiment recently developed by the PI as well as a course on Chromatographic Separation Processes. Finally, simulations performed in this project, as well as conceptual parts of molecular interactions will motivate new aspects of the Molecularium project, which uses animation movies to teach and inspire students at all levels about the fascinating world of molecules.

0933169Cramer 这项由化学和生物分离项目颁发的 NSF 奖项支持伦斯勒理工学院的 Steven Cramer 教授及其同事 Shekhar Garde 和 Curt Breneman 的工作，以更深入地了解多模式 (MM) 色谱系统中的选择性本质。该项目将采用最先进的新型多模式配体和材料库以及蛋白质库来详细研究 MM 配体-蛋白质相互作用。将使用 NMR 研究游离溶液 MM 配体与一组标记模型蛋白质的结合，以确定结合动力学和蛋白质上的配体结合位点。对天然蛋白质进行化学修饰，以产生具有各种表面特性组合的多种蛋白质梯。将在一系列操作条件下使用这些蛋白质以及一组市售蛋白质进行色谱实验，以研究蛋白质保留行为并确定这些 MM 系统的适当等温线模型。为了补充实验，将进行溶液中蛋白质-配体结合的大规模MD模拟，以及蛋白质-多模式树脂相互作用的粗粒度建模方法。这些模拟将提供有关配体结合位点、结合模式以及溶液中相互作用的动力学和热力学的数据。 MD 和粗粒度模拟也将提供重要的数据，用于生成新颖的分子描述符。将使用色谱数据和新颖的分子描述符来确定蛋白质亲和力和等温线参数的预测定量结构特性关系（QSPR）模型。拟议的项目将对用于蛋白质纯化的MM色谱技术的开发和实施产生重大影响。这项工作将促进下一代 MM 色谱系统的设计，并将为 MM 色谱提供预测工具，从而促进这些系统纯化生物治疗药物的方法开发。改进的MM色谱系统的开发将有可能减少纯化治疗性蛋白质所需的下游处理步骤的数量，从而降低生物制药的生产成本。此外，具有独特选择性的多模式分离系统将为质谱分析蛋白质提供新的前端分离。最后，更深入地了解蛋白质与各类多模式配体和表面的相互作用模式将对分离以外的领域（包括生物材料、生物传感器和药物发现）产生潜在影响。拟议的研究还将对化学工程研究生和本科生的教育产生重要影响。拟议的研究将在生物技术和跨学科研究中心进行，该中心为研究生和本科生提供良好的多学科培训机会。学生将接触细胞培养、溶液核磁共振波谱、色谱、分子模拟和化学计量学。该项目的研究成果也将被纳入PI最近开发的化学工程高级实验室色谱实验以及色谱分离过程课程中。最后，该项目中进行的模拟以及分子相互作用的概念部分将激发分子项目的新方面，该项目使用动画电影来教导和启发各个级别的学生了解迷人的分子世界。