分子动力学
结合亲和力
化学
合理设计
机制(生物学)
稳定器(航空)
计算生物学
亲缘关系
血浆蛋白结合
药品
杠杆(统计)
分子结合
小分子
生物物理学
分子识别
功能(生物学)
药物发现
蛋白质-蛋白质相互作用
分子力学
计算化学
组合化学
结合位点
纳米技术
药物设计
生物系统
选择性
对接(动物)
分子模型
理论(学习稳定性)
伞式取样
计算机科学
过程(计算)
装订袋
蛋白质稳定性
蛋白质功能
药物开发
作用机理
作者
Kexin Xu,Mingyun Shen,Zhe Wang,Sutong Xiang,Qirui Deng,Kaimo Yang,Zhiliang Jiang,Zihao Wang,Chen Yin,Tingjun Hou,Huiyong Sun
标识
DOI:10.1021/acs.jcim.5c02966
摘要
Molecular glues, including protein degraders and protein-protein interaction (PPI) stabilizers, have emerged as a new paradigm of drug design for regulating interactions between biomacromolecules; yet it is still a challenge for rational design of molecular glues. KRAS, as a prevalent oncogenic driver, is notoriously difficult to target by traditional small molecular drugs due to its challenging binding surface and frequent mutations. Although the small molecular drug RMC7977 has been designed as a PPI stabilizer for stabilizing the inherently weak RAS-CYPA interaction, the precise molecular mechanism underlying its stabilization effect and selectivity difference requires a deeper understanding. To this end, we leverage an integrated computational strategy combining molecular dynamics (MD) simulation, end-point binding free-energy calculation, and enhanced sampling technologies to elucidate the dynamic characteristics of RAS-ligand-CYPA interactions. Our result exhibits a high correlation between the predicted binding affinities and the experimental observations, demonstrating that RMC7977, acting as a strong PPI stabilizer, significantly enhances the stability of the KRAS-CYPA interaction, where, by delicately remodeling the protein-protein interface, the drug optimizes various interactions. Moreover, the results also uncover the dynamic process of stabilizer-mediated KRAS-CYPA stabilization and the mechanistic origin of the binding selectivity. This study provides essential molecular-level insights into RMC7977's function and offers a valuable computational framework for evaluating the stabilization effect of ligands targeting the KRAS-CYPA and other challenging PPI systems.
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