EzSEA: an interactive web interface for enzyme sequence evolution analysis
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...
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Published in | Bioinformatics advances Vol. 5; no. 1; p. vbaf118 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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England
2025
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ISSN | 2635-0041 2635-0041 |
DOI | 10.1093/bioadv/vbaf118 |
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Abstract | 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/. |
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AbstractList | 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.MotivationEnzymes 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.ResultsWe 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/.Availability and implementationEzSEA is freely available on the web at https://jianglabnlm.com/ezsea/. 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/. |
Author | Jiang, Angela K Jiang, Xiaofang Zhao, Jerry |
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