Muli Christine S, Xie Dan, Post Carol Beth, Trader Darci J
Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, 575 West Stadium Avenue, West Lafayette, Indiana 47907, United States.
Department of Pharmaceutical Sciences, University of California- Irvine, 856 Health Sciences, Irvine, California 92697, United States.
J Am Chem Soc. 2025 Jul 15. doi: 10.1021/jacs.5c04064.
Ligand discovery of nonenzymatic proteins can be accomplished through screening methods utilizing libraries comprising small molecules, peptides, and peptidomimetics. Incorporating peptoids, which are oligomers of -substituted glycine monomers, into high-throughput screens can produce libraries of large structural diversity. Due to their malleable structures, peptoids can occupy unique protein binding sites, but determination of the peptoid binding pose is challenging. For example, the peptoid KDT-11 is reported to bind with low micromolar binding affinity to the proteasome subunit Rpn-13. Poor solubility of initial compound screening hits, like KDT-11, can greatly hinder progress in drug discovery since it limits in vitro characterization. The work reported here overcomes this hurdle with the addition of a solubility tag to KDT11, enabling elucidation of the biologically relevant surface of the peptoid through a variety of structure-activity relationships and biophysical studies. NMR paramagnetic relaxation data guided a structural modeling protocol using multiple molecular dynamics (MD) trajectories and extensive sampling. The final peptoid-protein structure is conformationally stable in equilibrium MD trajectories for >1 μs time period. KDT-11 binds across the β6/β7/β8 strands and α-helix of Rpn-13, revealing an interface for inhibition that could be targeted in future computational drug discovery efforts to obtain more potent ligands for Rpn-13. It is reasonable that the methodology described here can extend to other flexible peptoid or peptide ligands in complexes with proteins.
非酶蛋白的配体发现可以通过利用包含小分子、肽和拟肽的文库的筛选方法来实现。将由α-取代甘氨酸单体组成的寡聚物类肽纳入高通量筛选中,可以产生具有高度结构多样性的文库。由于类肽具有可塑性结构,它们可以占据独特的蛋白质结合位点,但确定类肽的结合构象具有挑战性。例如,据报道类肽KDT-11与蛋白酶体亚基Rpn-13的结合亲和力为低微摩尔级别。像KDT-11这样的初始化合物筛选命中物的低溶解度会极大地阻碍药物发现的进展,因为它限制了体外表征。本文报道的工作通过给KDT11添加一个溶解度标签克服了这一障碍,通过各种构效关系和生物物理研究,能够阐明类肽的生物学相关表面。核磁共振顺磁弛豫数据指导了一个使用多个分子动力学(MD)轨迹和广泛采样的结构建模方案。最终的类肽-蛋白质结构在平衡MD轨迹中在超过1微秒的时间段内构象稳定。KDT-11跨Rpn-13的β6/β7/β8链和α-螺旋结合,揭示了一个抑制界面,在未来的计算药物发现工作中可以将其作为靶点,以获得针对Rpn-13的更有效配体。这里描述的方法能够扩展到与蛋白质形成复合物的其他柔性类肽或肽配体是合理的。