Jiang Angela K, Zhao Jerry, Jiang Xiaofang
Center of Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20740, United States.
National Library of Medicine, National Institutes of Health, Bethesda, MD 20892, United States.
Bioinform Adv. 2025 May 20;5(1):vbaf118. doi: 10.1093/bioadv/vbaf118. eCollection 2025.
Enzymes catalyze essential chemical reactions, driving metabolism, immunity, and growth. Understanding their evolution requires identifying mutations that shaped their functions and substrate interactions. Current methods lack integration of evolutionary history and intuitive visualization tools.
We develop Enzyme Sequence Evolution Analysis (EzSEA), a web interface that identifies putative functionally important mutations by performing the following steps: structural prediction, homology search, multiple sequence alignment and trimming, phylogenetic tree inference, ancestral sequence reconstruction, and enzyme delineation. The EzSEA web application enables intuitive visualization of results, highlighting key mutations and phylogenetic tree branches that putatively delineate the enzyme of interest. Finally, we validate EzSEA by identifying previously experimentally verified key mutations in the gut bacteria enzyme bilirubin reductase.
EzSEA is freely available on the web at https://jianglabnlm.com/ezsea/.
酶催化基本化学反应,驱动新陈代谢、免疫和生长。了解它们的进化需要识别塑造其功能和底物相互作用的突变。目前的方法缺乏进化历史的整合和直观的可视化工具。
我们开发了酶序列进化分析(EzSEA),这是一个网络界面,通过执行以下步骤识别推定的功能重要突变:结构预测、同源性搜索、多序列比对和修剪、系统发育树推断、祖先序列重建和酶的划定。EzSEA网络应用程序能够直观地可视化结果,突出显示推定划定感兴趣酶的关键突变和系统发育树分支。最后,我们通过识别肠道细菌酶胆红素还原酶中先前经实验验证的关键突变来验证EzSEA。
EzSEA可在网站https://jianglabnlm.com/ezsea/上免费获取。