Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Department of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Bioinformatics. 2022 Dec 13;38(24):5413-5420. doi: 10.1093/bioinformatics/btac704.
The 'glycoEnzymes' include a set of proteins having related enzymatic, metabolic, transport, structural and cofactor functions. Currently, there is no established ontology to describe glycoEnzyme properties and to relate them to glycan biosynthesis pathways.
We present GlycoEnzOnto, an ontology describing 403 human glycoEnzymes curated along 139 glycosylation pathways, 134 molecular functions and 22 cellular compartments. The pathways described regulate nucleotide-sugar metabolism, glycosyl-substrate/donor transport, glycan biosynthesis and degradation. The role of each enzyme in the glycosylation initiation, elongation/branching and capping/termination phases is described. IUPAC linear strings present systematic human/machine-readable descriptions of individual reaction steps and enable automated knowledge-based curation of biochemical networks. All GlycoEnzOnto knowledge is integrated with the Gene Ontology biological processes. GlycoEnzOnto enables improved transcript overrepresentation analyses and glycosylation pathway identification compared to other available schema, e.g. KEGG and Reactome. Overall, GlycoEnzOnto represents a holistic glycoinformatics resource for systems-level analyses.
https://github.com/neel-lab/GlycoEnzOnto.
Supplementary data are available at Bioinformatics online.
“糖基酶”包括一组具有相关酶学、代谢、运输、结构和辅因子功能的蛋白质。目前，还没有建立描述糖基酶特性并将其与聚糖生物合成途径联系起来的本体论。
我们提出了 GlycoEnzOnto，这是一个描述 403 个人类糖基酶的本体论，这些酶沿着 139 条糖基化途径、134 种分子功能和 22 种细胞区室进行了分类。所描述的途径调节核苷酸糖代谢、糖基供体/底物转运、聚糖生物合成和降解。描述了每种酶在糖基化起始、延伸/分支和加帽/终止阶段的作用。IUPAC 线性字符串提供了个体反应步骤的系统的人类/机器可读描述，并能够实现基于知识的生化网络的自动分类。GlycoEnzOnto 的所有知识都与基因本体论生物过程集成在一起。与其他可用模式（如 KEGG 和 Reactome）相比，GlycoEnzOnto 能够实现改进的转录物过表达分析和糖基化途径识别。总的来说，GlycoEnzOnto 代表了一个用于系统水平分析的整体糖基化信息学资源。
https://github.com/neel-lab/GlycoEnzOnto。
补充数据可在生物信息学在线获得。
