Oberg Nils, Precord Timothy W, Mitchell Douglas A, Gerlt John A
Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, Illinois 61801, United States.
Department of Chemistry, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, Illinois 61801, United States.
ACS Bio Med Chem Au. 2022 Feb 16;2(1):22-35. doi: 10.1021/acsbiomedchemau.1c00048. Epub 2021 Dec 17.
The radical SAM superfamily (RSS), arguably the most functionally diverse enzyme superfamily, is also one of the largest with ~700K members currently in the UniProt database. The vast majority of the members have uncharacterized enzymatic activities and metabolic functions. In this Perspective, we describe RadicalSAM.org, a new web-based resource that enables a user-friendly genomic enzymology strategy to explore sequence-function space in the RSS. The resource attempts to enable identification of isofunctional groups of radical SAM enzymes using sequence similarity networks (SSNs) and the genome context of the bacterial, archaeal, and fungal members provided by genome neighborhood diagrams (GNDs). Enzymatic activities and functions frequently can be inferred from genome context given the tendency for genes of related function to be clustered. We invite the scientific community to use RadicalSAM.org to guide their experimental studies to discover new enzymatic activities and metabolic functions, contribute experimentally verified annotations to RadicalSAM.org to enhance the ability to predict novel activities and functions, and provide suggestions for improving this resource.
自由基S-腺苷甲硫氨酸超家族(RSS)可以说是功能最多样化的酶超家族,也是目前UniProt数据库中最大的超家族之一,约有70万个成员。绝大多数成员具有未表征的酶活性和代谢功能。在本观点文章中,我们介绍了RadicalSAM.org,这是一个新的基于网络的资源,它能实现一种用户友好的基因组酶学策略,以探索RSS中的序列-功能空间。该资源试图利用序列相似性网络(SSN)以及基因组邻域图(GND)提供的细菌、古菌和真菌成员的基因组背景,来识别自由基SAM酶的同功能基团。鉴于相关功能的基因有聚集的趋势,酶活性和功能通常可以从基因组背景中推断出来。我们邀请科学界使用RadicalSAM.org来指导他们的实验研究,以发现新的酶活性和代谢功能,为RadicalSAM.org贡献经实验验证的注释,以增强预测新活性和功能的能力,并为改进该资源提供建议。