Group Proposal: Rational Protein Bioprocessing with Hydrophobic Separations

本项目的目的是开发一种定量工具，可用于预测色谱性能作为给定蛋白质混合物/介质/移动的相组合的吸附蛋白质结构的函数，并选择/设计疏水介质和移动的相条件。 该工具将促进疏水介质的工艺规模使用，从而产生更简单，更强大的工艺，降低新的和非专利蛋白质药物的商品成本和上市时间。 该项目将通过解决以下具体目标来推动疏水色谱系统的发展：（2）使用定量结构保留关系（QSRR）关联线性和非线性蛋白质-介质相互作用行为，以将蛋白质保留与天然蛋白质、扰动蛋白质的描述符联系起来，表面和溶液的物理性质，（3）发展了一个基本的理论，蛋白质介质相互作用使用朗之万偶极子方法来计算蛋白质表面的优先相互作用系数（PIC），和（4）通过将蛋白质-介质相互作用的QSRR相关性和/或PIC理论与宏观/微观模型相结合，该项目是卡内基梅隆大学、伦斯勒理工学院和弗吉尼亚大学的研究人员在生物化学工程、应用生物物理学、色谱分离、热力学建模和计算化学方面的专业知识的共同努力。这种合作，与团队座谈会，实验室轮换和工业实习的建议定期计划，预计将提供一个丰富的研究和教育环境的学生和教师一样。

The objective of this project is the development of a quantitative tool that can be used to predict chromatographic performance as a function of adsorbed protein structure for given protein mixture/media/mobile phase combinations and to select/design hydrophobic media and mobile phase conditions. This tool will promote the process-scale use of hydrophobic media, resulting in simpler, more robust processes that reduce cost-of-goods and time-to-market for new and off-patent protein drugs. This project will advance the state of the art of hydrophobic chromatographic systems by addressing the following specific aims: (1) validate generic mechanisms for protein unfolding on adsorption to hydrophobic chromatographic media, (2) correlate linear and nonlinear protein-media interaction behavior using quantitative structure retention relationships (QSRRs) to connect protein retention to descriptors of native protein, perturbed protein, surface and solution physical properties, (3) develop a fundamental theory for protein-media interactions using a Langevin dipole approach to calculate protein-surface preferential interaction coefficients (PICs), and (4) predict chromatographic performance for complex mixtures by coupling QSRR correlations and/or PIC theory for protein-media interactions with a macroscopic/engineering description of chromatographic operation.This project is a collaborative effort among researchers at Carnegie Mellon University, Rensselaer Polytechnic Institute and the University of Virginia with expertise in biochemical engineering, applied biophysics, chromatographic separations, and thermodynamic modeling and computational chemistry. This collaboration, with the proposed regular program of team colloquia, laboratory rotations and industrial internships, is expected to provide a rich research and educational environment for the students and faculty alike.