Production & Crystallization of Membrane Protein for 3D Structure

翻译后摘要：这项建议解决了真核蛋白表达，溶解，稳定和 晶化我们将通过整合蛋白质质量的早期评估测量来实现这一目标， 在现有的稳健的哺乳动物细胞表达平台中进行定量。这种方法结合了小说的使用， 快速测量第二维里的高通量自相互作用色谱系统（HT-SIC） 膜蛋白与一组特殊设计的添加剂混合的系数。人工神经 网络分析实验得出的第二维里系数数据，并进行计算机预测， 改善蛋白质溶解度和均一性的新的溶液条件。HT-SIC系统还能够 对改变蛋白质-蛋白质相互作用的溶液条件进行知情调整， 提高了生产高质量晶体的能力。实现这一建议的具体目标将提供 研究社区，朝着具有成本效益的，以知识为基础的方法取得重大进展， 表达、纯化、稳定和结晶膜蛋白。 靶蛋白包括两种离子通道蛋白（上皮钠通道，ENaC和囊泡钠通道， 纤维化跨膜调节蛋白，CFTR），两个GPCR（趋化因子受体-1，CCR1和鞘氨醇- 1磷酸盐受体（S1P）和生长激素受体（GHR）。这些蛋白质的结构 有助于我们了解它们的生物学作用机制和在几个方面的作用。 重要疾病包括癌症（结肠癌、乳腺癌和前列腺癌）、糖尿病、囊性纤维化、生长异常， 免疫系统紊乱高血压败血症和流感对于每个IMP，我们都建立了合作关系， 与生物化学家/生物学家一起，他们对每种靶蛋白都有长期的兴趣和经验， 其蛋白质相互作用体。

Abstract: This proposal addresses challenges in eukaryotic protein expression, solublization, stablization and crystallization. We will accomplish this by integrating early assessment measurements of protein quality and quantity into an existing robust mammalian cell expression platform. This approach integrates use of a novel high-throughput self-interaction chromatography system (HT-SIC) that rapidly measures second virial coefficients for the membrane protein mixed with a specially designed panel of additives. An artificial neural network analyzes the experimentally derived second virial coefficient data and performs in silico predictions of novel solution conditions that improve protein solubility and homogeneity. The HT-SIC system also enables informed adjustments to solution conditions that alter protein-protein interactions such that the probability of producing high-quality crystals is improved. Achieving the specific aims of this proposal will provide the research community with significant advancements toward a cost effective, knowledge-based approach to express, purify, stabilize and crystallize membrane proteins. Target proteins include two ion channel proteins (epithelial sodium channel, ENaC and cystic fibrosis transmembrane regulator protein, CFTR), two GPCRs (chemokine receptor-1, CCR1 and sphingosine- 1 phosphate receptor, S1P) and growth hormone receptor, GHR. Structures of these proteins would contribute significantly to our understanding of their biological mechanism of action and role in several important diseases including cancer (colon, breast and prostate), diabetes, cystic fibrosis, growth anomalies, immune system disorders, hypertension, sepsis and the flu. For each IMP, we have established collaborations with biochemists/biologists with a long-standing interest in and experience working with each target protein and its protein interactome.