Raman Srivatsan
Department of Biochemistry and Department of Bacteriology, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
Biochemistry. 2018 Jan 30;57(4):376-382. doi: 10.1021/acs.biochem.7b01094. Epub 2018 Jan 8.
The study of allostery has a central place in biology because of the myriad roles of allosteric proteins in cellular function. As technologies for probing the spatiotemporal resolution of biomolecules have become increasingly sophisticated, so has our understanding of the diverse structural and molecular mechanisms of allosteric proteins. Studies have shown that the allosteric signal is transmitted a through a network of residue-residue interactions connecting distal sites on a protein. Linking structural and dynamical changes to the functional role of individual residues will give a more complete molecular view of allostery. In this work, we highlight new mutational technologies that enable a systems-level, quantitative description of allostery that dissect the role of individual residues through large-scale functional screens. A molecular model for predicting allosteric hot spots can be developed by applying statistical tools on the resulting large sequence-structure-function data sets. Design of allosteric proteins with new function is essential for engineering biological systems. Previous design efforts demonstrate that the allosteric network is a powerful functional constraint in the design of novel or enhanced allosteric proteins. We discuss how a priori knowledge of an allosteric network could improve rational design by facilitating better navigation of the design space. Understanding the molecular "rules" governing allostery would elucidate the molecular basis of dysfunction in disease-associated allosteric proteins, provide a means for designing tailored therapeutics, and enable the design of new sensors and enzymes for synthetic biology.
由于变构蛋白在细胞功能中发挥着众多作用，变构研究在生物学中占据核心地位。随着探测生物分子时空分辨率的技术日益复杂，我们对变构蛋白多样的结构和分子机制的理解也不断深入。研究表明，变构信号通过连接蛋白质上远端位点的残基-残基相互作用网络进行传递。将结构和动态变化与单个残基的功能作用联系起来，将能更全面地从分子层面理解变构现象。在这项工作中，我们重点介绍了新的突变技术，这些技术能够对变构进行系统层面的定量描述，通过大规模功能筛选剖析单个残基的作用。通过对所得的大量序列-结构-功能数据集应用统计工具，可以开发出预测变构热点的分子模型。设计具有新功能的变构蛋白对于构建生物系统至关重要。以往的设计工作表明，变构网络在设计新型或增强型变构蛋白时是一种强大的功能限制因素。我们讨论了变构网络的先验知识如何通过促进更好地在设计空间中导航来改进合理设计。理解支配变构的分子“规则”将阐明疾病相关变构蛋白功能障碍的分子基础，提供设计定制疗法的方法，并为合成生物学设计新的传感器和酶。
