BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins

被引:651
作者
van Heel, Auke J. [1 ]
de Jong, Anne [1 ]
Song, Chunxu [1 ]
Viel, Jakob H. [1 ]
Kok, Jan [1 ]
Kuipers, Oscar P. [1 ]
机构
[1] Univ Groningen, Mol Genet, GBB, NL-9747 AG Groningen, Netherlands
基金
欧盟地平线“2020”;
关键词
CHEMICAL-STRUCTURES; PREDICTION; GENES;
D O I
10.1093/nar/gky383
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Interest in secondary metabolites such as RiPPs (ri-bosomally synthesized and posttranslationally modified peptides) is increasing worldwide. To facilitate the research in this field we have updated our mining web server. BAGEL4 is faster than its predecessor and is now fully independent from ORFcalling. Gene clusters of interest are discovered using the core-peptide database and/or through HMM motifs that are present in associated context genes. The databases used for mining have been updated and extended with literature references and links to UniProt and NCBI. Additionally, we have included automated promoter and terminator prediction and the option to upload RNA expression data, which can be displayed along with the identified clusters. Further improvements include the annotation of the context genes, which is now based on a fast blast against the prokaryote part of the UniRef90 database, and the improved web-BLAST feature that dynamically loads structural data such as internal cross-linking from UniProt. Overall BAGEL4 provides the user with more information through a user-friendly webinterface which simplifies data evaluation. BAGEL4 is freely accessible at http://bagel4.molgenrug.nl.
引用
收藏
页码:W278 / W281
页数:4
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