MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

By B. Terlouw, Kai Blin, J. Navarro-Muñoz, Nicole E. Avalon, M. Chevrette, Susan Egbert, Sanghoon Lee, David Meijer, Michael J J Recchia, Zachary L. Reitz and 72 more. Nucleic Acids Res., 2022

357 citations recorded by the source corpus.

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

Subfields: Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/b4d175445ef6fc76f93260a7e56b8b2103d48156

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Pharmacology

Citations in the corpus

Artificial Intelligence For Natural Product Drug Discovery (2023, background): “Alternatively, repositories can offer validation reports, quality metrics, prevalence statistics (for example, the statistics page of MIBiG 4 that facilitates cross-species comparisons of biosynthetic potential) and other feedback on data to depositors that provides a tangible and immediate benefit ”