The specificity landscape of bacterial ribonuclease P.
The specificity landscape of bacterial ribonuclease P.
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DOI：
10.1016/j.jbc.2023.105498
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发表时间：
2024-01
影响因子：
4.8
通讯作者：
Harris, Michael E
中科院分区：
文献类型：
--
作者：
Chamberlain, Alexandra R;Huynh, Loc;Huang, Wei;Taylor, Derek J;Harris, Michael E
开发RNA加工酶底物特异性的定量模型是理解其生物学和指导生物技术和生物医学应用的关键一步。最理想的是，模型预测相对速率常数的替代基板应集成的理解的结构结合到“快”和“慢”的基板，大型数据集的速率常数的替代基板，和转录组数据识别在体内加工网站的酶。这些数据对于细菌核糖核蛋白RNase P是可用的或正在出现的，RNase P是一种广泛的和必需的tRNA 5′加工内切酶，因此使其成为研究生物特异性原理的有价值的模型系统。事实上，细菌RNase P的良好结构和动力学使得能够开发tRNA变体速率常数的高通量测量，并为定量特异性建模提供必要的框架。一些研究记录了前体tRNA底物以及细菌RNase P的RNA和蛋白质亚基在结合过程中构象变化的重要性，尽管功能作用和动力学仍在解决中。最近，大肠杆菌RNase P与替代前体tRNA的冷冻电镜研究结果揭示了构象变化和底物特异性之间的潜在机制关系。然而，仍然存在广泛的未知领域，包括利用这些进展进行药物发现，实现RNase P底物的完整核算，以及了解细胞环境如何有助于体内RNA加工特异性。
Developing quantitative models of substrate specificity for RNA processing enzymes is a key step toward understanding their biology and guiding applications in biotechnology and biomedicine. Optimally, models to predict relative rate constants for alternative substrates should integrate an understanding of structures of the enzyme bound to “fast” and “slow” substrates, large datasets of rate constants for alternative substrates, and transcriptomic data identifying in vivo processing sites. Such data are either available or emerging for bacterial ribonucleoprotein RNase P a widespread and essential tRNA 5′ processing endonuclease, thus making it a valuable model system for investigating principles of biological specificity. Indeed, the well-established structure and kinetics of bacterial RNase P enabled the development of high throughput measurements of rate constants for tRNA variants and provided the necessary framework for quantitative specificity modeling. Several studies document the importance of conformational changes in the precursor tRNA substrate as well as the RNA and protein subunits of bacterial RNase P during binding, although the functional roles and dynamics are still being resolved. Recently, results from cryo-EM studies of E. coli RNase P with alternative precursor tRNAs are revealing prospective mechanistic relationships between conformational changes and substrate specificity. Yet, extensive uncharted territory remains, including leveraging these advances for drug discovery, achieving a complete accounting of RNase P substrates, and understanding how the cellular context contributes to RNA processing specificity in vivo.