拟肽
化学
肽
侧链
计算生物学
配体(生物化学)
药物发现
组合化学
系留
蛋白质-蛋白质相互作用
小分子
结合位点
立体化学
生物化学
受体
细胞生物学
聚合物
有机化学
生物
作者
Ashley E. Modell,Frank Marrone,Nihar R. Panigrahi,Yingkai Zhang,Paramjit S. Arora
摘要
Constrained peptides have proven to be a rich source of ligands for protein surfaces, but are often limited in their binding potency. Deployment of nonnatural side chains that access unoccupied crevices on the receptor surface offers a potential avenue to enhance binding affinity. We recently described a computational approach to create topographic maps of protein surfaces to guide the design of nonnatural side chains [J. Am. Chem. Soc. 2017, 139, 15560]. The computational method, AlphaSpace, was used to predict peptide ligands for the KIX domain of the p300/CBP coactivator. KIX has been the subject of numerous ligand discovery strategies, but potent inhibitors of its interaction with transcription factors remain difficult to access. Although the computational approach provided a significant enhancement in the binding affinity of the peptide, fine-tuning of nonnatural side chains required an experimental screening method. Here we implement a peptide-tethering strategy to screen fragments as nonnatural side chains on conformationally defined peptides. The combined computational-experimental approach offers a general framework for optimizing peptidomimetics as inhibitors of protein-protein interactions.
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