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结构生物学中的质量管理方法:用于成功结晶的蛋白质的生物物理筛选。

An approach to quality management in structural biology: biophysical selection of proteins for successful crystallization.

作者信息

Niesen Frank H, Koch Anja, Lenski Ulf, Harttig Ulrich, Roske Yvette, Heinemann Udo, Hofmann Klaus Peter

机构信息

Institut für Medizinische Physik und Biophysik, Charité Universitätsmedizin Berlin, D-10117 Berlin, Germany.

出版信息

J Struct Biol. 2008 Jun;162(3):451-9. doi: 10.1016/j.jsb.2008.03.007. Epub 2008 Mar 25.

Abstract

Aggregation, incorrect folding and low stability are common obstacles for protein structure determination, and are often discovered at a very late state of protein production. In many cases, however, the reasons for failure to obtain diffracting crystals remain entirely unknown. We report on the contribution of systematic biophysical characterization to the success in structural determination of human proteins of unknown fold. Routine analysis using dynamic light scattering (DLS), differential scanning calorimetry (DSC) and Fourier-transform infrared spectroscopy (FTIR) was employed to evaluate fold and stability of 263 purified protein samples (98 different human proteins). We found that FTIR-monitored temperature scanning may be used to detect incorrect folding and discovered a positive correlation between unfolding enthalpy measured with DSC and the size of small, globular proteins that may be used to estimate the quality of protein preparations. Furthermore, our work establishes that the risk of aggregation during concentration of proteins may be reduced through DLS monitoring. In summary, our study demonstrates that biophysical characterization provides an ideal tool to facilitate quality management for structural biology and many other areas of biological research.

摘要

聚集、错误折叠和低稳定性是蛋白质结构测定的常见障碍,且往往在蛋白质生产的后期才被发现。然而,在许多情况下,未能获得衍射晶体的原因仍然完全未知。我们报告了系统生物物理表征对未知折叠的人类蛋白质结构测定成功的贡献。使用动态光散射(DLS)、差示扫描量热法(DSC)和傅里叶变换红外光谱(FTIR)进行常规分析,以评估263个纯化蛋白质样品(98种不同的人类蛋白质)的折叠和稳定性。我们发现,FTIR监测的温度扫描可用于检测错误折叠,并发现用DSC测量的解折叠焓与小的球状蛋白质大小之间存在正相关,这可用于估计蛋白质制剂的质量。此外,我们的工作表明,通过DLS监测可以降低蛋白质浓缩过程中的聚集风险。总之,我们的研究表明,生物物理表征为促进结构生物学和许多其他生物学研究领域的质量管理提供了理想工具。

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