蛋白质-RNA识别与相互作用在细胞生命活动中发挥着核心作用，静态结构难以解释其发挥功能的全部机制，动力学性质与其功能行使密切相关。项目拟发展基于全原子和粗粒化模型的有效分析蛋白质-RNA相互作用动力学行为的方法，包括二面角互信息方法、针对结构常常较松散RNA的考虑相互作用多尺度和离子效应的弹性网络模型(ENM)方法、基于ENM的残基微扰和迭代方法。针对代表性体系研究离子等因素对识别动力学影响的规律和机制，分析稳定结构和序列特异性识别模式的主要因素并探讨其中的竞争与协同效应；研究蛋白质/RNA拓扑结构及固有动力学性质与功能性构象变化之间的关系，进而模拟变构随时间的演化过程并识别变构信号传导通路及关键位点，探讨蛋白质/RNA对彼此结合的响应并揭示局部结构扰动扩散导致功能性变构的物理机制。项目有助于揭示蛋白质-RNA动力学与特异性识别和功能行使之间的关系，关键位点识别可为药物设计提供重要依据。

Protein-RNA recognition and interactions play a central role in cellular life activities. It is very difficult for static structures to explain all the mechanisms of their function exertion. Dynamic properties are closely related to the exertion of their functions. The aim of the project is to develop theoretical methods to effectively analyze the dynamic behavior of protein-RNA interactions based on all-atom and coarse-grained models, which include the dihedral mutual information method, the elastic network model (ENM) method for usually loose RNAs with the effects of multiple interaction scales and ions considered, and the ENM-based residual perturbation and iterative methods. For the representative protein-RNA systems, we will study the law and mechanism of the influence of ions and other factors on the recognition dynamics, analyze the main factors of stabilizing the structure- and sequence-specific recognition patterns and discuss the effects of competition and cooperation involved in them. We are going to study the relationship between protein/RNA topological structure, intrinsic dynamical properties and functionally conformational changes, thereout simulate the time evolution behavior of the conformational changes and identify the allosteric signal transduction pathways and key sites, and explore the response of protein/RNA to the binding to each other, revealing the physical mechanism of functionally conformational changes caused by the local site perturbation and its diffusion. The project helps to reveal the relationship between protein-RNA interaction dynamics and the specific recognition, the execution of biological functions. The identification of key sites can provide important information for drug design.