Conformational sub-states in enzyme catalysis: Applications to ribonuclease

描述（由申请人提供）：酶通过充当将反应物聚集在一起的支架来执行催化化学反应的指定功能。一个多世纪以来，结构在酶功能中的作用已经为人所知；然而，最近的证据表明，在环境生理条件下，功能酶存在于一系列构象中。从酶结构的整体观点来看，它可以检测出具有促进结构和动力学特征的功能的构象亚态。此外，来自实验和计算模型的证据表明，这些构象亚态之间的转换可以实现底物识别和催化。对这些功能相关的子状态的定量分析仍然具有挑战性，特别是由于所涉及的时间尺度范围广，单个技术的分辨率窗口有限，以及一些子状态可能潜在的事实

DESCRIPTION (provided by applicant): Enzymes perform the designated function of catalyzing chemical reactions by serving more than a scaffold for bringing together the reactants. The role of structure in enzyme function has been known for more than a century now; however, more recent evidence suggests that a functioning enzyme exists in an ensemble of conformations under ambient physiological conditions. The ensemble view of enzyme structure suggests that it can sample conformational sub-states that exhibit function promoting structural and dynamical features. Further, evidence from experiments and computational modeling suggest that transitions between these conformational sub-states enable substrate recognition and catalysis. Quantitative insights into these functionally relevant sub-states remains challenging, particularly due to the wide range of time-scales involved, limited window of resolution for individual techniques and the fact that some of the sub-states can be potentially short-lived. We address these issues by developing a joint computational-experimental framework to identify and characterize such functionally relevant sub-states in the context of enzyme function. In addition to identifying structural intermediates, our framework will quantify the relative population of the conformations in various sub-states as well as enable their linkage to kinetics of enzyme function through the catalytic cycle. This integrated approach will be used to investigate the bio-medically relevant ribonuclease (RNase) family of proteins and enzymes. In particular, we will: (1) Develop a theoretical framework to identify and characterize the multi-scale hierarchy in the conformational landscape of proteins; (2) Utilize the developed framework to investigate the RNase fold members and their ability to access distinct conformational sub-states, including functionally relevant sub-states along the catalytic cycle; (3) Validate the developed model and predicted sub- states by integrating nuclear magnetic resonance (NMR) relaxation dispersion experiments. The developed methodology and models will be improved by iterative interaction between the 3 PIs with different expertise spanning theoretical biophysics, computational simulations and experimental techniques. Overall, our studies will have implications in the design of novel inhibitors of RNase function in the context of neurotoxicity, angiogenesis and anti-pathogenicity.