Статья

dbCAN3: automated carbohydrate-active enzyme and substrate annotation

Jinfang ZhengNebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska , Lincoln , NE 68588, USAQiwei GeSchool of Computing, University of Nebraska , Lincoln , NE 68588, USAYuchen YanNebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska , Lincoln , NE 68588, USAXinpeng ZhangNebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska , Lincoln , NE 68588, USALe HuangCurriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill , NC , USAYanbin YinNebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska , Lincoln , NE 68588, USA

2023en

ABI

Аннотация

Carbohydrate active enzymes (CAZymes) are made by various organisms for complex carbohydrate metabolism. Genome mining of CAZymes has become a routine data analysis in (meta-)genome projects, owing to the importance of CAZymes in bioenergy, microbiome, nutrition, agriculture, and global carbon recycling. In 2012, dbCAN was provided as an online web server for automated CAZyme annotation. dbCAN2 (https://bcb.unl.edu/dbCAN2) was further developed in 2018 as a meta server to combine multiple tools for improved CAZyme annotation. dbCAN2 also included CGC-Finder, a tool for identifying CAZyme gene clusters (CGCs) in (meta-)genomes. We have updated the meta server to dbCAN3 with the following new functions and components: (i) dbCAN-sub as a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level; (ii) searching against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substates of the dbCAN-PUL database for substrate prediction at the CGC level; (iii) a majority voting method to consider all CAZymes with substrate predicted from dbCAN-sub for substrate prediction at the CGC level; (iv) improved data browsing and visualization of substrate prediction results on the website. In summary, dbCAN3 not only inherits all the functions of dbCAN2, but also integrates three new methods for glycan substrate prediction.

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Идентификаторы

DOI: 10.1093/nar/gkad328

Цитирования и источники

Цитирований: 3Использованных источников: 0

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