Bio2Rxn: sequence-based enzymatic reaction predictions by a consensus strategy

• Published in: Bioinformatics 2020-06, Vol.36 (11), p.3600-3601
• Main Authors: Zhang, Tong, Tian, Yu, Yuan, Le, Chen, Fu, Ren, Ailin, Hu, Qian-Nan
• Format: Article
• Language: English
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btaa135

Abstract Summary The development of sequencing technologies has generated large amounts of protein sequence data. The automated prediction of the enzymatic reactions of uncharacterized proteins is a major challenge in the field of bioinformatics. Here, we present Bio2Rxn as a web-based tool to provide putative enzymatic reaction predictions for uncharacterized protein sequences. Bio2Rxn adopts a consensus strategy by incorporating six types of enzyme prediction tools. It allows for the efficient integration of these computational resources to maximize the accuracy and comprehensiveness of enzymatic reaction predictions, which facilitates the characterization of the functional roles of target proteins in metabolism. Bio2Rxn further links the enzyme function prediction with more than 300 000 enzymatic reactions, which were manually curated by more than 100 people over the past 9 years from more than 580 000 publications. Availability and implementation Bio2Rxn is available at: http://design.rxnfinder.org/bio2rxn/. Contact [e-mail] Supplementary information Supplementary data are available at Bioinformatics online.