Barnett Christopher B, Senapathi Tharindu, Naidoo Kevin J
Scientific Computing Research Unit and Department of Chemistry, University of Cape Town, Rondebosch, 7701, South Africa.
Infectious Disease and Molecular Medicine, Faculty of Health Science, University of Cape Town, Rondebosch, 7701, South Africa.
Beilstein J Org Chem. 2020 Oct 13;16:2540-2550. doi: 10.3762/bjoc.16.206. eCollection 2020.
When faced with the investigation of the preferential binding of a series of ligands against a known target, the solution is not always evident from single structure analysis. An ensemble of structures generated from computer simulations is valuable; however, visual analysis of the extensive structural data can be overwhelming. Rapid analysis of trajectory data, with tools available in the Galaxy platform, can be used to understand key features and compare differences that inform the preferential ligand structure that favors binding. We illustrate this informatics approach by investigating the in-silico binding of a peptide and glycopeptide epitope of the glycoprotein Mucin 1 (MUC1) binding with the antibody AR20.5. To study the binding, we performed molecular dynamics simulations using OpenMM and then used the Galaxy platform for data analysis. The same analysis tools are applied to each of the simulation trajectories and this process was streamlined by using Galaxy workflows. The conformations of the antigens were analyzed using root-mean-square deviation, end-to-end distance, Ramachandran plots, and hydrogen bonding analysis. Additionally, RMSF and clustering analysis were carried out. These analyses were used to rapidly assess key features of the system, interrogate the dynamic structure of the ligand, and determine the role of glycosylation on the conformational equilibrium. The glycopeptide conformations in solution change relative to the peptide; thus a partially pre-structuring is seen prior to binding. Although the bound conformation of peptide and glycopeptide is similar, the glycopeptide fluctuates less and resides in specific conformers for more extended periods. This structural analysis which gives a high-level view of the features in the system under observation, could be readily applied to other binding problems as part of a general strategy in drug design or mechanistic analysis.
当面临一系列配体与已知靶点的优先结合情况的研究时，仅通过单一结构分析往往无法明确解决方案。通过计算机模拟生成的一组结构很有价值；然而，对大量结构数据进行可视化分析可能会让人应接不暇。利用Galaxy平台中可用的工具对轨迹数据进行快速分析，可用于了解关键特征并比较差异，从而为有利于结合的优先配体结构提供信息。我们通过研究糖蛋白粘蛋白1（MUC1）的肽和糖肽表位与抗体AR20.5的计算机模拟结合情况，来说明这种信息学方法。为了研究这种结合，我们使用OpenMM进行了分子动力学模拟，然后使用Galaxy平台进行数据分析。将相同的分析工具应用于每个模拟轨迹，并通过使用Galaxy工作流程简化了这一过程。使用均方根偏差、端到端距离、拉氏图和氢键分析对抗原的构象进行了分析。此外，还进行了均方根波动（RMSF）和聚类分析。这些分析用于快速评估系统的关键特征，探究配体的动态结构，并确定糖基化对构象平衡的作用。溶液中的糖肽构象相对于肽会发生变化；因此在结合之前可以看到部分预构象。尽管肽和糖肽的结合构象相似，但糖肽的波动较小，并且在特定构象中停留的时间更长。这种能对观察到的系统特征进行高层次观察的结构分析，作为药物设计或机理分析的一般策略的一部分，可以很容易地应用于其他结合问题。
