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A Combined NMR and Computational Approach to Investigate Peptide Binding to a Designed Armadillo Repeat Protein

机译:结合核磁共振和计算方法来研究肽与设计的犰狳重复蛋白的结合

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The specific recognition of peptide sequences by proteins plays an important role both in biology and in diagnostic applications. Here we characterize the relatively weak binding of the peptide neurotensin (NT) to the previously developed Armadillo repeat protein VG_328 by a multidisciplinary approach based on solution NMR spectroscopy, mutational studies, and molecular dynamics (MD) simulations, totaling 20 mu s for all MD runs. We describe assignment challenges arising from the repetitive nature of the protein sequence, and we present novel approaches to address them. Partial assignments obtained for VG_328 in combination with chemical shift perturbations allowed us to identify the repeats not involved in binding. Their subsequent elimination resulted in a reduced-size binder with very similar affinity for NT, for which near-complete backbone assignments were achieved. A binding mode suggested by automatic docking and further validated by explicit solvent MD simulations is consistent with paramagnetic relaxation enhancement data collected using spin-labeled NT. Favorable intermolecular interactions are observed in the MD simulations for the residues that were previously shown to contribute to binding in an Ala scan of NT. We further characterized the role of residues within the N-cap for protein stability and peptide binding. Our multidisciplinary approach demonstrates that an initial low-resolution picture for a low-micromolar-peptide binder can be refined through the combination of NMR, protein design, docking, and MD simulations to establish its binding mode, even in the absence of crystallographic data, thereby providing valuable information for further design. (C) 2015 Elsevier Ltd. All rights reserved.
机译:蛋白质对肽序列的特异性识别在生物学和诊断应用中都起着重要作用。在这里,我们通过基于溶液NMR光谱,突变研究和分子动力学(MD)模拟的多学科方法,对肽神经降压素(NT)与先前开发的犰狳重复蛋白VG_328的相对弱结合进行了表征,所有MD总计20μs运行。我们描述了由蛋白质序列的重复性质引起的分配挑战,并且我们提出了解决这些挑战的新颖方法。 VG_328的部分分配与化学位移扰动相结合,使我们能够识别不参与结合的重复序列。他们随后的淘汰导致了对NT具有非常相似亲和力的尺寸减小的粘合剂,为此实现了近乎完整的骨架分配。自动对接建议的结合模式,并通过显式溶剂MD模拟进一步验证的结合模式与使用自旋标记NT收集的顺磁弛豫增强数据一致。在MD模拟中观察到有利的分子间相互作用,这些残基先前显示在NT的Ala扫描中有助于结合。我们进一步表征了N-帽内残基对蛋白质稳定性和肽结合的作用。我们的多学科方法表明,即使没有晶体学数据,也可以通过NMR,蛋白质设计,对接和MD模拟的组合来完善低微摩尔肽结合剂的初始低分辨率图片,以建立其结合模式,从而为进一步设计提供有价值的信息。 (C)2015 Elsevier Ltd.保留所有权利。

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