Relating Protein Structure to Stability in the Solution and Adsorbed Phases

提案编号：0731055主要研究者：Erik Fernandez研究机构：哥伦比亚大学提案标题：蛋白质结构与溶液和吸附相的稳定性该项目的目标是建立蛋白质在溶液中的结构和分子特性与其在疏水作用色谱（HIC）表面上的展开行为之间的预测关系。研究工作有三个要素：实验、计算和建模。 第一个目的是测量批量吸附，色谱法，和氢-氘同位素交换（HX），以建立相关的平衡，动力学和结构方面的一组单域和多域蛋白质在不同的吸附剂表面。将对溶液中和表面上的溶剂辅料的残留水平进行比较，以揭示不同环境下局部稳定性倾向的预期模式。第二个目的是匹配这些实验检测到的模式与预测的局部稳定性的解决方案计算的COREX软件的基础上统计力学合奏的蛋白质构象，以确认其能力，获得分布的microstateenergy。第三个目标是制定合奏条款的四态模型，已成功地在相关的静态和动态的稳定性行为，这样的吸附系统，并使用实验和模拟结果，以开发强大的蛋白质吸附和稳定性的关系。预期的结果是提供预测蛋白质何时以及如何在吸附后展开的技术，包括阐明局部不稳定区域。 这种预测能力最直接和关键的应用是治疗性蛋白质纯化。在这种情况下，从治疗性蛋白质中去除错误折叠、未折叠和聚集的蛋白质变得越来越重要。这些预测工具最终将使工艺开发工程师能够最大限度地减少天然蛋白质的解折叠，并最大限度地提高折叠和错误折叠或解折叠蛋白质之间的选择性。控制蛋白质在表面上的行为是药物输送、生物材料、生物传感器、蛋白质阵列和纳米级器件的核心。在所有这些情况下，控制蛋白质吸附的程度和速率、蛋白质构象的变化和聚集的出现是至关重要的。 通过弗吉尼亚大学工程多样性中心招募的本科生将参与这项研究。多学科合作与教授文森特希尔泽（美国）。德克萨斯医学分支）将使研究生和本科生都能应用重要的生物物理和统计力学方法来解决具有基础和实际重要性的问题。与支持生物制药公司的合作互动将为工作提供相关的多域蛋白质，将结果传播给从业者，并使学生在商业相关的背景下接触蛋白质吸附和稳定性问题。最后，将开发一个新的生物化学工程课程模块，以纳入本研究的各个方面，包括计算和建模活动。该模块将通过与圣何塞州立大学联合建立的电子期刊网站传播给其他化学工程学院。

PROPOSAL NUMBER: 0731055PRINCIPAL INVESTIGATOR: Erik FernandezINSTITUTION: University of VirginiaPROPOSAL TITLE: Relating Protein Structure to Stability in the Solution and Adsorbed PhasesThe goal of the project is to establish predictive relationships between the structural and molecular properties of proteins in solution and their unfolding behavior on hydrophobic interaction chromatography (HIC) surfaces. There are three elements of the research effort: experiment, computation, and modeling. The first aim is measuring batch adsorption, chromatography, and hydrogen-deuterium isotope exchange (HX) to establish the relevant equilibrium, kinetic, and structural aspects of a set of single and multidomain proteins on different adsorbent surfaces. Residue-level comparisons of solvent accessibilities in solutions and on surfaces will be made to reveal expected patterns of local stability propensities under the different environments. The second aim is to match these experimentally detected patterns with predicted local stabilities in solution computed by the COREX software based on statistical mechanical ensembles of protein conformation to confirm its capability for obtaining distributions of microstateenergies. The third aim is to formulate in ensemble terms a four-state modelthat has been successful in correlating static and dynamic stability behavior of such adsorbing systems, and use the experimental and simulated results to develop robust relationships for protein adsorption and stability. The intended outcome is to providetechniques for predicting when and how proteins unfold upon adsorption, includingelucidation of local regions of instability. The most direct and critical application of such a predictive capability is to therapeutic protein purification. In that context, removing misfolded, unfolded, and aggregated protein from therapeutic proteins is of growing importance. These predictive tools will ultimately enable process development engineers to minimize unfolding of native protein and maximize selectivity between folded and misfolded or unfolded proteins. Controlling the behavior of proteins on surfaces is central to drug delivery, biomaterials, biosensors, protein arrays, and nanoscale devices. In all of these situations, controlling the degree and rate of protein adsorption, the changes in protein conformation, and the appearance of aggregation are critical. Undergraduates recruited through the University of Virginia Center for Diversity in Engineering will participate in the research. A multidisciplinary collaboration with Prof. Vincent Hilser (U. Texas Medical Branch) will enable both graduate and undergraduate students to apply important biophysical and statistical mechanical approaches to problems of fundamental and practical importance. Collaborative interactions with supporting biopharmaceutical companies will provide relevant multidomain proteins for the work, disseminate the results to practitioners, and expose students to protein adsorption and stability issues in a commercially relevant context. Finally, a new module for biochemical engineering courses will be developed to incorporate aspects of this research, including computational and modeling activities. This module will be disseminated to other chemical engineering faculty via an electronic journal website being set up jointly with San Jose State University.