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结合湿实验室和干实验室技术以指导含大卷曲螺旋蛋白的结晶

Combining Wet and Dry Lab Techniques to Guide the Crystallization of Large Coiled-coil Containing Proteins.

作者信息

Zalewski Jenna K, Heber Simone, Mo Joshua H, O'Conor Keith, Hildebrand Jeffrey D, VanDemark Andrew P

机构信息

Department of Biological Sciences, University of Pittsburgh.

Department of Biological Sciences, University of Pittsburgh; Institute of Structural Biology, German Research Center for Environmental Health.

出版信息

J Vis Exp. 2017 Jan 6(119):54886. doi: 10.3791/54886.

Abstract

Obtaining crystals for structure determination can be a difficult and time consuming proposition for any protein. Coiled-coil proteins and domains are found throughout nature, however, because of their physical properties and tendency to aggregate, they are traditionally viewed as being especially difficult to crystallize. Here, we utilize a variety of quick and simple techniques designed to identify a series of possible domain boundaries for a given coiled-coil protein, and then quickly characterize the behavior of these proteins in solution. With the addition of a strongly fluorescent tag (mRuby2), protein characterization is simple and straightforward. The target protein can be readily visualized under normal lighting and can be quantified with the use of an appropriate imager. The goal is to quickly identify candidates that can be removed from the crystallization pipeline because they are unlikely to succeed, affording more time for the best candidates and fewer funds expended on proteins that do not produce crystals. This process can be iterated to incorporate information gained from initial screening efforts, can be adapted for high-throughput expression and purification procedures, and is augmented by robotic screening for crystallization.

摘要

对于任何蛋白质而言,获取用于结构测定的晶体可能都是一项困难且耗时的工作。卷曲螺旋蛋白和结构域在自然界中广泛存在,然而,由于它们的物理性质和聚集倾向,传统上认为它们特别难以结晶。在此,我们运用了多种快速且简单的技术,旨在为给定的卷曲螺旋蛋白确定一系列可能的结构域边界,然后迅速表征这些蛋白在溶液中的行为。通过添加一种强荧光标签(mRuby2),蛋白质表征变得简单直接。目标蛋白在正常光照下即可轻松可视化,并且可以使用合适的成像仪进行定量。目标是快速识别那些不太可能成功从而可以从结晶流程中剔除的候选蛋白,为最有潜力的候选蛋白留出更多时间,并减少在无法产生晶体的蛋白上的资金投入。这个过程可以反复进行以纳入从初步筛选工作中获得的信息,可以适用于高通量表达和纯化程序,并且通过机器人结晶筛选得到加强。

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