Department of Chemistry, University of Massachusetts, Amherst, Massachusetts 01003, United States.
Department of Biochemistry and Molecular Biology, University of Massachusetts, Amherst, Massachusetts 01003, United States.
J Phys Chem B. 2022 Sep 15;126(36):6780-6791. doi: 10.1021/acs.jpcb.2c03806. Epub 2022 Aug 30.
Hsp70 molecular chaperones play central roles in maintaining a healthy cellular proteome. Hsp70s function by binding to short peptide sequences in incompletely folded client proteins, thus preventing them from misfolding and/or aggregating, and in many cases holding them in a state that is competent for subsequent processes like translocation across membranes. There is considerable interest in predicting the sites where Hsp70s may bind their clients, as the ability to do so sheds light on the cellular functions of the chaperone. In addition, the capacity of the Hsp70 chaperone family to bind to a broad array of clients and to identify accessible sequences that enable discrimination of those that are folded from those that are not fully folded, which is essential to their cellular roles, is a fascinating puzzle in molecular recognition. In this article we discuss efforts to harness computational modeling with input from experimental data to develop a predictive understanding of the promiscuous yet selective binding of Hsp70 molecular chaperones to accessible sequences within their client proteins. We trace how an increasing understanding of the complexities of Hsp70-client interactions has led computational modeling to new underlying assumptions and design features. We describe the trend from purely data-driven analysis toward increased reliance on physics-based modeling that deeply integrates structural information and sequence-based functional data with physics-based binding energies. Notably, new experimental insights are adding to our understanding of the molecular origins of "selective promiscuity" in substrate binding by Hsp70 chaperones and challenging the underlying assumptions and design used in earlier predictive models. Taking the new experimental findings together with exciting progress in computational modeling of protein structures leads us to foresee a bright future for a predictive understanding of selective-yet-promiscuous binding exploited by Hsp70 molecular chaperones; the resulting new insights will also apply to substrate binding by other chaperones and by signaling proteins.
热休克蛋白 70 分子伴侣在维持健康的细胞蛋白质组中发挥核心作用。热休克蛋白通过与不完全折叠的客户蛋白中的短肽序列结合来发挥作用,从而防止它们错误折叠和/或聚集,并在许多情况下使它们处于能够进行后续过程(如跨膜易位)的状态。预测热休克蛋白可能与其客户结合的位点具有相当大的意义,因为这样做可以揭示伴侣的细胞功能。此外,热休克蛋白伴侣家族能够结合广泛的客户,并识别可访问的序列,从而区分已折叠和未完全折叠的序列,这对于其细胞功能至关重要,这是分子识别中的一个迷人难题。在本文中,我们讨论了利用计算建模和实验数据输入来开发对热休克蛋白分子伴侣与客户蛋白中可访问序列的混杂但选择性结合的预测性理解的努力。我们追溯了对热休克蛋白-客户相互作用复杂性的日益理解如何导致计算建模采用新的基本假设和设计特征。我们描述了从纯粹基于数据的分析向更依赖基于物理的建模的趋势,这种建模方法深度整合了结构信息和基于序列的功能数据以及基于物理的结合能。值得注意的是,新的实验见解增加了我们对 HSP70 伴侣在底物结合中“选择性混杂”的分子起源的理解,并挑战了早期预测模型中使用的基本假设和设计。将新的实验发现与蛋白质结构计算建模的令人兴奋的进展结合起来,使我们对 HSP70 分子伴侣利用的选择性但混杂的结合的预测性理解有一个光明的未来;由此产生的新见解也将适用于其他伴侣和信号蛋白的底物结合。