1Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bldg. 10/Rm 8C-101, Bethesda, MD 20892 USA.
2Center for Molecular Modeling, Center for Information Technology, Bldg. 12/Rm 2049, Bethesda, MD 20892 USA.
Commun Biol. 2019 Sep 13;2:338. doi: 10.1038/s42003-019-0585-1. eCollection 2019.
Protein-protein interaction (PPI) networks are known to be valuable targets for therapeutic intervention; yet the development of PPI modulators as next-generation drugs to target specific vertices, edges, and hubs has been impeded by the lack of structural information of many of the proteins and complexes involved. Building on recent advancements in cross-linking mass spectrometry (XL-MS), we describe an effective approach to obtain relevant structural data on R7BP, a master regulator of itch sensation, and its interfaces with other proteins in its network. This approach integrates XL-MS with a variety of modeling techniques to successfully develop antibody inhibitors of the R7BP and RGS7/Gβ5 duplex interaction. Binding and inhibitory efficiency are studied by surface plasmon resonance spectroscopy and through an R7BP-derived dominant negative construct. This approach may have broader applications as a tool to facilitate the development of PPI modulators in the absence of crystal structures or when structural information is limited.
蛋白质-蛋白质相互作用 (PPI) 网络已被证实是治疗干预的有价值的靶点;然而,由于涉及的许多蛋白质和复合物缺乏结构信息,因此将 PPI 调节剂开发为针对特定顶点、边缘和枢纽的下一代药物受到了阻碍。基于交联质谱 (XL-MS) 的最新进展,我们描述了一种有效的方法来获得瘙痒感觉主调节剂 R7BP 及其与网络中其他蛋白质相互作用的相关结构数据。该方法将 XL-MS 与多种建模技术相结合,成功开发了 R7BP 和 RGS7/Gβ5 二聚体相互作用的抗体抑制剂。通过表面等离子体共振光谱和 R7BP 衍生的显性负构想来研究结合和抑制效率。该方法可能具有更广泛的应用,可作为一种工具,在没有晶体结构或结构信息有限的情况下,促进 PPI 调节剂的开发。