antiSMASH

antiSMASH identifies and annotates biosynthetic gene clusters to characterize secondary metabolite pathways in bacterial and fungal genomes.

Key Features:

• Comprehensive cluster detection: Identifies biosynthetic loci across known secondary metabolite classes including polyketides, non-ribosomal peptides, terpenes, aminoglycosides, oligosaccharide antibiotics, phenazines, and others.
• Algorithm integration: Incorporates algorithms such as ClusterFinder for unknown cluster detection, CASSIS for boundary prediction, SANDPUMA for substrate specificity prediction, and ClusterBlast for cluster and sub-cluster comparison and dereplication.
• Enzyme- and domain-level annotation: Provides enzyme-level annotation with active-site pinpointing, domain-level alignments, and assignment of Enzyme Commission numbers for functional classification.
• Chemical structure prediction: Predicts chemical structures including reduction states in polyketides and provides enhanced structure-prediction outputs.
• Input and sequence support: Supports multi-FASTA, GenBank, and EMBL input formats and direct protein sequence analysis.
• Plug-and-play architecture: Implements a modular architecture that allows integration of new predictor and output modules.
• Database resources: Links to precomputed gene cluster data via antiSMASH-DB for comparison against high-quality microbial genome clusters.
• Integration with in silico methods: Cross-links numerous gene-specific in silico tools and consolidates multiple pattern-matching and prediction methods.

Scientific Applications:

• Drug discovery: Enables genome mining for novel antibiotics, chemotherapeutics, and other bioactive natural products such as anti-tumor agents and cholesterol-lowering compounds.
• Natural product discovery: Facilitates identification and characterization of secondary metabolite biosynthetic pathways for novel compound discovery.
• Agricultural biotechnology: Supports discovery and analysis of microbial metabolites relevant to crop protection and agricultural applications.
• Chemical biology and biosynthetic pathway analysis: Provides annotations and predictions to elucidate enzymatic functions, substrate specificities, and biosynthetic logic in microbial pathways.

Methodology:

Uses sequence alignment, probabilistic algorithms and curated pattern-matching procedures (including ClusterFinder, CASSIS, SANDPUMA, and ClusterBlast), aligns identified regions to known databases, assigns Enzyme Commission numbers, performs enzyme- and domain-level annotation with active-site identification, and predicts chemical structures including polyketide reduction states.