分子动力学中配体轨迹的可视化分析

Adam Jurcík, K. Furmanová, J. Byška, Vojtěch Vonásek, O. Vávra, Pavol Ulbrich, H. Hauser, B. Kozlíková
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引用次数: 1

摘要

在许多情况下,蛋白质与其他小分子(配体)的反应发生在深埋的活性位点。当研究这些类型的反应时,生物化学家检查配体运动的轨迹是至关重要的。这些轨迹是用计算机方法预测的,可以产生可能轨迹的大集合。在本文中,我们提出了一种新的方法来对大配体轨迹集进行交互式视觉探索和分析,使领域专家能够基于轨迹特性来理解蛋白质的功能。提出的解决方案由多个链接的2D和3D视图组成,能够以明智的方式进行交互式探索和轨迹过滤。在工作流程中,我们专注于特定于配体轨迹的交互式可视化分析的实际方面。我们采用小倍数原则,将过多的轨迹分解成更容易分析的小块。我们描述了如何使用钻取技术来创建和存储具有所需属性的轨迹选择,从而实现多个数据集的比较。在适当设计的2D和3D视图中,生物化学家既可以观察单个轨迹,也可以选择将信息汇总到功能箱线图或密度可视化中。我们的解决方案基于与领域专家的紧密合作,旨在尽可能多地满足他们的需求。我们的新方法的有用性通过两个案例研究证明,由合作的蛋白质工程师进行。
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Visual Analysis of Ligand Trajectories in Molecular Dynamics
In many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.
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