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使用人工智能增强的综合生物物理研究准确表征HSP90伴侣蛋白抑制剂的结合动力学和变构机制

Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies.

作者信息

Xu Chao, Zhang Xianglei, Zhao Lianghao, Verkhivker Gennady M, Bai Fang

机构信息

Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China.

Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States.

出版信息

JACS Au. 2024 Apr 1;4(4):1632-1645. doi: 10.1021/jacsau.4c00123. eCollection 2024 Apr 22.

Abstract

The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs , leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure-kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate constant (), enabling a direct assessment of the drug-target residence time. These models demonstrated good predictive performance, where hydrophobic and hydrogen bond interactions significantly influence the prediction. In subsequent applications, our models were used to assist in the discovery of new inhibitors for the N-terminal domain of HSP90α (N-HSP90α), demonstrating predictive capabilities on an experimental validation set with a new scaffold. In X-ray crystallography experiments, the loop-middle conformation of N-HSP90α was observed for the first time (previously, the loop-middle conformation had only been observed in -N-HSP90α structures). Interestingly, we observed different conformations of N-HSP90α simultaneously in an asymmetric unit, which was also observed in a -N-HSP90α structure, suggesting an equilibrium of conformations between different states in solution, which could be one of the determinants affecting the binding kinetics of the ligand. Different ligands can undergo conformational selection or alter the equilibrium of conformations, inducing conformational rearrangements and resulting in different effects on binding kinetics. We then used molecular dynamics simulations to describe conformational changes of N-HSP90α in different conformational states. In summary, the study of the binding kinetics and molecular mechanisms of N-HSP90α provides valuable information for the development of more targeted therapeutic approaches.

摘要

药物与其靶点的结合动力学逐渐被视为药物疗效的关键指标,这促使近年来开发了各种预测结合动力学的计算方法。然而,与结合亲和力的预测相比,结合动力学的潜在结构和动态决定因素更为复杂。目前仍缺乏高效准确的结合动力学预测方法。在本研究中,利用132种靶向热休克蛋白90α(HSP90α)ATP结合域的抑制剂建立了定量结构-动力学关系(QSKR)模型,以预测解离速率常数(),从而能够直接评估药物-靶点的驻留时间。这些模型表现出良好的预测性能,其中疏水和氢键相互作用对预测有显著影响。在后续应用中,我们的模型被用于协助发现HSP90α N端结构域(N-HSP90α)的新抑制剂,在具有新支架的实验验证集上展示了预测能力。在X射线晶体学实验中,首次观察到N-HSP90α的环-中间构象(此前,环-中间构象仅在-N-HSP90α结构中观察到)。有趣的是,我们在一个不对称单元中同时观察到了N-HSP90α的不同构象,这在-N-HSP90α结构中也有观察到,表明溶液中不同状态之间存在构象平衡,这可能是影响配体结合动力学的决定因素之一。不同的配体可以进行构象选择或改变构象平衡,诱导构象重排并导致对结合动力学的不同影响。然后,我们使用分子动力学模拟来描述N-HSP90α在不同构象状态下的构象变化。总之,对N-HSP90α结合动力学和分子机制的研究为开发更具针对性的治疗方法提供了有价值的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66c0/11040708/561adc179cfc/au4c00123_0001.jpg

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