ResiDEM:利用密度聚类进行动态残基识别的同构差分电子密度图分析工具

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Sriram Srinivasa Raghavan,  and , Osamu Miyashita*, 
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引用次数: 0

摘要

生物分子的时间分辨串行飞秒晶体学(TR-SFX)可捕捉晶体结构中残余运动的时间演化动态,使结构变化对化学和物理刺激的响应可视化,从而阐明所研究系统的结构与功能之间的关系。然而,由于系统的大小、时间和空间的复杂性以及远离活性位点的异构行为等各种因素,对残余运动的解释可能非常复杂。仅仅依靠电子密度图可视化也会给区分有用数据和无关数据带来挑战。为了准确识别残基并确定它们各自对反应动力学的贡献,我们需要新的工具。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,并将它们与近端残基联系起来。它可以识别具有显著运动的残基并对其进行排序。网络表示法可用于描述运动残基之间的相互关系。借助这些功能,ResiDEM 可帮助解释 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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

ResiDEM: Analytical Tool for Isomorphous Difference Electron Density Maps Utilizing Dynamic Residue Identification via Density Clustering

ResiDEM: Analytical Tool for Isomorphous Difference Electron Density Maps Utilizing Dynamic Residue Identification via Density Clustering

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.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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