Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario, Canada.
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario, Canada; Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada.
Biophys J. 2022 Jun 7;121(11):2035-2045. doi: 10.1016/j.bpj.2022.05.004. Epub 2022 May 10.
Allosteric regulation is essential to control biological function. In addition, allosteric sites offer a promising venue for selective drug targeting. However, accurate mapping of allosteric sites remains challenging since allostery relies on often subtle, yet functionally relevant, structural and dynamical changes. A viable approach proposed to overcome such challenge is chemical shift covariance analysis (CHESCA). Although CHESCA offers an exhaustive map of allosteric networks, it is critical to define the core allosteric sites to be prioritized in subsequent functional studies or in the design of allosteric drugs. Here, we propose two new CHESCA-based methodologies, called temperature CHESCA (T-CHESCA) and CLASS-CHESCA, aimed at narrowing down allosteric maps to the core allosteric residues. Both T- and CLASS-CHESCAs rely on the invariance of core inter-residue correlations to changes in the chemical shifts of the active and inactive conformations interconverting in fast exchange. In T-CHESCA the chemical shifts of such states are modulated through temperature changes, while in CLASS-CHESCA through variations in the spin-active nuclei involved in pairwise correlations. T- and CLASS-CHESCAs, as well as complete-linkage CHESCA, were applied to the cAMP-binding domain of the exchange protein directly activated by cAMP (EPAC), which serves as a prototypical allosteric switch. Residues consistently identified by the three CHESCA methods were found in previously identified EPAC allosteric core sites. Hence, T-, CLASS-, and CL-CHESCA provide a toolset to establish allosteric site hierarchy and triage allosteric sites to be further analyzed by mutations and functional assays. Furthermore, the core allosteric networks selectively revealed through T- and CLASS-CHESCA are expected to facilitate the mechanistic understanding of disease-related mutations and the design of selective allosteric modulators.
变构调节对于控制生物功能至关重要。此外,变构位点为选择性药物靶向提供了一个有前途的场所。然而,由于变构依赖于通常微妙但功能相关的结构和动力学变化,因此准确映射变构位点仍然具有挑战性。一种可行的方法是化学位移协方差分析(CHESCA)。虽然 CHESCA 提供了变构网络的详尽图谱,但定义核心变构位点以优先在随后的功能研究或变构药物设计中进行仍然至关重要。在这里,我们提出了两种新的基于 CHESCA 的方法,称为温度 CHESCA(T-CHESCA)和 CLASS-CHESCA,旨在将变构图谱缩小到核心变构残基。T-和 CLASS-CHESCAs 都依赖于核心残基间相关性在活性和非活性构象之间快速交换时化学位移变化的不变性。在 T-CHESCA 中,通过改变温度来调节这些状态的化学位移,而在 CLASS-CHESCA 中则通过涉及成对相关的自旋活性核的变化来调节。T-CHESCA 和 CLASS-CHESCA 以及完全链接 CHESCA 被应用于环腺苷酸结合域的交换蛋白直接激活的环腺苷酸(EPAC),它作为一个典型的变构开关。通过三种 CHESCA 方法一致识别的残基位于先前鉴定的 EPAC 变构核心位点中。因此,T-、CLASS-和 CL-CHESCA 提供了一种工具集,可以建立变构位点层次结构,并通过突变和功能测定进一步分析变构位点。此外,通过 T-和 CLASS-CHESCA 选择性揭示的核心变构网络有望促进对与疾病相关的突变的机制理解和选择性变构调节剂的设计。