Abstract
Natural products originating from microorganisms are frequently used in antimicrobial and anticancer drugs, pesticides, herbicides or fungicides. In the last years, the increasing availability of microbial genome data has made it possible to access the wealth of biosynthetic clusters responsible for the production of these compounds by genome mining. antiSMASH is one of the most popular tools in this field. The antiSMASH database provides pre-computed antiSMASH results for many publicly available microbial genomes and allows for advanced cross-genome searches. The current version 2 of the antiSMASH database contains annotations for 6200 full bacterial genomes and 18,576 bacterial draft genomes and is available at https://antismash-db.secondarymetabolites.org/.
Highlights
A majority of antibacterial and antifungal drugs, as well as drugs for many other indications, are derived from microbial natural products (1)
As many secondary metabolite biosynthetic gene cluster contain repetitive sequences, this implies that many biosynthetic gene clusters (BGCs) end up being split on multiple contigs without any linkage information, leading to low-quality
The antiSMASH database 2 contains BGCs identified in 6,200 full genomes and adds 18 draft genomes
Summary
A majority of antibacterial and antifungal drugs, as well as drugs for many other indications, are derived from microbial natural products (1). The increasing availability of genomic data in the last two decades allows us to complement these approaches with genome mining to identify and characterize biosynthetic pathways for natural products in genome and metagenome data (2). Since its initial release in 2011, antiSMASH (6–9) has established itself as a standard tool for secondary metabolite genome mining and is currently the most widely used software pipeline for this task. AntiSMASH uses a rule-based cluster detection approach to identify 45 different types of secondary metabolite biosynthetic pathways via their core biosynthetic enzymes. Type I polyketides, terpenes, lanthipeptides, thiopeptides, sactipeptides and lassopeptides, antiSMASH can provide more detailed predictions of the compounds produced by the respective biosynthetic gene clusters (BGCs). Secondary metabolite clusters of orthologous group (smCoG) classification is used to assign functions to gene products in the predicted BGCs
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