Curvature of designed armadillo repeat proteins allows modular peptide binding

Curvature of designed armadillo repeat proteins allows modular peptide binding
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DOI:
10.1016/j.jsb.2017.08.009
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发表时间:
2018-02-01
影响因子:
3
通讯作者:
Pluckthun, Andreas
Pluckthun, Andreas
中科院分区:
生物学3区
文献类型:
--
作者:
Hansen, Simon;Ernst, Patrick;Pluckthun, Andreas

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设计的犰狳重复序列蛋白(dArmRPs)被开发用于创建模块化肽结合技术,其中每个结构重复序列结合靶肽的两个残基。这种技术的基本先决条件是与肽键长度匹配的dArmRP几何形状。为此,我们确定了一个大的集合(n = 27)的dArmRP X射线结构,其中12个是以前未公布的,计算曲率参数,定义其几何形状。我们的分析表明,共识dArmRPs表现出接近模块化肽识别的最佳范围的曲率。肽配体的结合可以诱导所需范围内的曲率,如通过溶液中的单分子FRET实验所证实的。另一方面,计算设计的ArmRP,其中侧链已经被选择以最佳地适合几何优化的骨架,在现实中变得更加发散,因此不适合连续的肽结合。此外,我们表明,晶格的形成可以诱导小,但显着的偏差,在解决方案中采用的曲率,这可能会干扰重复蛋白质支架的评价时,需要高精度。该研究证实了共有dArmRP作为开发模块化肽结合剂的支架的适用性。
Designed armadillo repeat proteins (dArmRPs) were developed to create a modular peptide binding technology where each of the structural repeats binds two residues of the target peptide. An essential prerequisite for such a technology is a dArmRP geometry that matches the peptide bond length. To this end, we determined a large set (n = 27) of dArmRP X-ray structures, of which 12 were previously unpublished, to calculate curvature parameters that define their geometry. Our analysis shows that consensus dArmRPs exhibit curvatures close to the optimal range for modular peptide recognition. Binding of peptide ligands can induce a curvature within the desired range, as confirmed by single molecule FRET experiments in solution. On the other hand, computationally designed ArmRPs, where side chains have been chosen with the intention to optimally fit into a geometrically optimized backbone, turned out to be more divergent in reality, and thus not suitable for continuous peptide binding. Furthermore, we show that the formation of a crystal lattice can induce small but significant deviations from the curvature adopted in solution, which can interfere with the evaluation of repeat protein scaffolds when high accuracy is required. This study corroborates the suitability of consensus dArmRPs as a scaffold for the development of modular peptide binders.