Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan.
RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148, Japan.
Acta Crystallogr D Struct Biol. 2017 Sep 1;73(Pt 9):757-766. doi: 10.1107/S2059798317010932. Epub 2017 Aug 15.
An alternative rational approach to improve protein crystals by using single-site mutation of surface residues is proposed based on the results of a statistical analysis using a compiled data set of 918 independent crystal structures, thereby reflecting not only the entropic effect but also other effects upon protein crystallization. This analysis reveals a clear difference in the crystal-packing propensity of amino acids depending on the secondary-structural class. To verify this result, a systematic crystallization experiment was performed with the biotin carboxyl carrier protein from Pyrococcus horikoshii OT3 (PhBCCP). Six single-site mutations were examined: Ala138 on the surface of a β-sheet was mutated to Ile, Tyr, Arg, Gln, Val and Lys. In agreement with prediction, it was observed that the two mutants (A138I and A138Y) harbouring the residues with the highest crystal-packing propensities for β-sheet at position 138 provided better crystallization scores relative to those of other constructs, including the wild type, and that the crystal-packing propensity for β-sheet provided the best correlation with the ratio of obtaining crystals. Two new crystal forms of these mutants were obtained that diffracted to high resolution, generating novel packing interfaces with the mutated residues (Ile/Tyr). The mutations introduced did not affect the overall structures, indicating that a β-sheet can accommodate a successful mutation if it is carefully selected so as to avoid intramolecular steric hindrance. A significant negative correlation between the ratio of obtaining amorphous precipitate and the crystal-packing propensity was also found.
提出了一种通过对表面残基进行单点突变来改善蛋白质晶体的合理方法,该方法基于对包含 918 个独立晶体结构的数据集进行统计分析的结果,从而反映了熵效应以及对蛋白质结晶的其他影响。该分析揭示了氨基酸在晶体堆积倾向方面存在明显的差异,这取决于二级结构类别。为了验证这一结果,我们用来自 Pyrococcus horikoshii OT3 的生物素羧基载体蛋白(PhBCCP)进行了系统的结晶实验。对 6 个单点突变进行了研究:位于β-折叠表面的 Ala138 突变为 Ile、Tyr、Arg、Gln、Val 和 Lys。与预测一致,观察到两个突变体(A138I 和 A138Y)中位于位置 138 的残基具有最高的β-折叠晶体堆积倾向,与其他构建体(包括野生型)相比,提供了更好的结晶评分,并且β-折叠的晶体堆积倾向与获得晶体的比例具有最佳相关性。获得了这两个突变体的两种新晶体形式,其衍射分辨率很高,与突变残基(Ile/Tyr)形成了新的包装界面。引入的突变没有影响整体结构,这表明如果β-折叠能够仔细选择以避免分子内空间位阻,则可以容纳成功的突变。还发现获得无定形沉淀物的比例与晶体堆积倾向之间存在显著的负相关。