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antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences

TLDR
This work presents the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view.
Abstract
Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins and others) It aligns the identified regions at the gene cluster level to their nearest relatives from a database containing all other known gene clusters, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view antiSMASH is available at http://antismashsecondarymetabolitesorg

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Journal ArticleDOI

antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline

TL;DR: AntiSMASH 5 adds detection rules for clusters encoding the biosynthesis of acyl-amino acids, β-lactones, fungal RiPPs, RaS-Ri PPs, polybrominated diphenyl ethers, C-nucleosides, PPY-like ketones and lipolanthines and provides more detailed predictions for type II polyketide synthase-encoding gene clusters.
Journal ArticleDOI

antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification.

TL;DR: The thoroughly updated antiSMASH version 4 is presented, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, and several usability features have been updated and improved.
Journal ArticleDOI

antiSMASH 6.0: improving cluster detection and comparison capabilities.

TL;DR: antiSMASH as mentioned in this paper is the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi, and it is updated version 6 of antiSMASH.
References
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Journal ArticleDOI

MUSCLE: multiple sequence alignment with high accuracy and high throughput

TL;DR: MUSCLE is a new computer program for creating multiple alignments of protein sequences that includes fast distance estimation using kmer counting, progressive alignment using a new profile function the authors call the log-expectation score, and refinement using tree-dependent restricted partitioning.
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TL;DR: Improvements to FastTree are described that improve its accuracy without sacrificing scalability, and FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments.
Journal ArticleDOI

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TL;DR: Pfam as discussed by the authors is a widely used database of protein families, containing 14 831 manually curated entries in the current version, version 27.0, and has been updated several times since 2012.
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