RIKEN Center for Computational Science, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
J Chem Inf Model. 2024 Oct 14;64(19):7565-7575. doi: 10.1021/acs.jcim.4c00858. Epub 2024 Sep 19.
Time-resolved serial femtosecond crystallography (TR-SFX) of biological molecules captures the time-evolved dynamics of the residual motions across crystal structures, enabling the visualization of structural changes in response to chemical and physical stimuli to elucidate the relationship between the structure and function of the system under study. However, interpretations of residual motions can be complex to deconvolute because of various factors such as the system's size, temporal and spatial complexity, and allosteric behavior away from active sites. Relying solely on electron density map visualization can also pose a challenge in differentiating between useful and irrelevant data. In order to accurately identify residues and determine their respective contributions to the reaction dynamics, new tools are needed. We developed a new tool, ResiDEM, which employs a clustering-based approach to group difference electron densities and associate them with proximal residues. It can identify and rank residues with significant motions. Network representation can be used to delineate the interrelations between the residues in motion. With these features, ResiDEM helps to interpret residual motions in TR-SFX data, identify key residues, and elucidate their roles in dynamic processes.
时间分辨连续飞秒晶体学（TR-SFX）可以捕获生物分子在晶体结构中残余运动的时变动力学，从而能够可视化结构变化对化学和物理刺激的响应，以阐明研究体系结构与功能之间的关系。然而，由于系统的大小、时空复杂性以及远离活性部位的变构行为等各种因素的影响，对残余运动的解释可能很复杂，难以解析。仅仅依靠电子密度图可视化也可能难以区分有用和无关的数据。为了准确识别残基并确定它们对反应动力学的各自贡献，需要新的工具。我们开发了一种新工具 ResiDEM，它采用基于聚类的方法对差异电子密度进行分组，并将其与邻近的残基相关联。它可以识别和对具有显著运动的残基进行排序。网络表示可用于描绘运动中的残基之间的相互关系。有了这些功能，ResiDEM 有助于解释 TR-SFX 数据中的残余运动，识别关键残基，并阐明它们在动态过程中的作用。
