Wagner G
Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115.
J Biomol NMR. 1993 Jul;3(4):375-85. doi: 10.1007/BF00176005.
During the last decade, solution structures of many small proteins have been solved by NMR. The size of proteins that are being analyzed by NMR seems to increase steadily. Protein structures up to 18 kD have been solved so far, and spectra of proteins up to 30 kD have been assigned. Thus, NMR emerges as an attractive technique, in particular for structural studies of proteins that cannot by crystallized. However, the application of the technology is limited by relaxation properties of the proteins. If relaxation would only be determined by Stokes-Einstein-type rotational diffusion, the effects of the molecular size on relaxation properties of proteins and thus on the performance of multi-dimensional multiple-resonance experiments could readily be estimated. From this perspective, solving two- or three-fold larger structures seems possible. However, most larger proteins exhibit serious line broadening due to aggregation or other still unknown effects. Sample conditioning to minimize these effects is presently the challenge in the work with large proteins.
在过去十年间，许多小蛋白的溶液结构已通过核磁共振（NMR）得以解析。目前，通过NMR分析的蛋白尺寸似乎在稳步增加。截至目前，分子量高达18 kD的蛋白结构已被解析，分子量高达30 kD的蛋白谱也已被归属。因此，NMR成为一种颇具吸引力的技术，尤其适用于无法结晶的蛋白的结构研究。然而，该技术的应用受到蛋白弛豫特性的限制。如果弛豫仅由斯托克斯 - 爱因斯坦型旋转扩散决定，那么分子大小对蛋白弛豫特性进而对多维多共振实验性能的影响就很容易估算。从这个角度来看，解析比现有结构大两到三倍的结构似乎是可行的。然而，大多数较大的蛋白由于聚集或其他未知效应而出现严重的谱线展宽。目前，在处理大蛋白时，如何进行样品预处理以尽量减少这些影响是一大挑战。
