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. 2025 Jul 7;53(W1):W32-W38.
doi: 10.1093/nar/gkaf334.

antiSMASH 8.0: extended gene cluster detection capabilities and analyses of chemistry, enzymology, and regulation

Kai Blin  1 , Simon Shaw  1 , Lisa Vader  1 , Judit Szenei  1 , Zachary L Reitz  2 , Hannah E Augustijn  3   4 , José D D Cediel-Becerra  5 , Valérie de Crécy-Lagard  5 , Robert A Koetsier  4 , Sam E Williams  1 , Pablo Cruz-Morales  1 , Sopida Wongwas  6 , Alejandro E Segurado Luchsinger  7   8 , Friederike Biermann  4   9 , Aleksandra Korenskaia  10 , Mitja M Zdouc  4 , David Meijer  4 , Barbara R Terlouw  4 , Justin J J van der Hooft  4   11 , Nadine Ziemert  10 , Eric J N Helfrich  9   12 , Joleen Masschelein  7   8 , Christophe Corre  6 , Marc G Chevrette  5 , Gilles P van Wezel  3 , Marnix H Medema  3   4 , Tilmann Weber  1
Affiliations

antiSMASH 8.0: extended gene cluster detection capabilities and analyses of chemistry, enzymology, and regulation

Kai Blin et al. Nucleic Acids Res. .

Abstract

Microorganisms synthesize small bioactive compounds through their secondary or specialized metabolism. Those compounds play an important role in microbial interactions and soil health, but are also crucial for the development of pharmaceuticals or agrochemicals. Over the past decades, advancements in genome sequencing have enabled the identification of large numbers of biosynthetic gene clusters directly from microbial genomes. Since its inception in 2011, antiSMASH (https://antismash.secondarymetabolites.org/), has become the leading tool for detecting and characterizing these gene clusters in bacteria and fungi. This paper introduces version 8 of antiSMASH, which has increased the number of detectable cluster types from 81 to 101, and has improved analysis support for terpenoids and tailoring enzymes, as well as improvements in the analysis of modular enzymes like polyketide synthases and nonribosomal peptide synthetases. These modifications keep antiSMASH up-to-date with developments in the field and extend its overall predictive capabilities for natural product genome mining.

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Conflict of interest statement

J.J.J.vdH. is member of the Scientific Advisory Board of NAICONS Srl, Milano, Italy and consults for Corteva Agriscience, Indianapolis, IN, USA. M.H.M. is a member of the Scientific Advisory Board of Hexagon Bio. All other authors declare to have no conflicts of interest.

Figures

Graphical Abstract
Graphical Abstract
Figure 1.
Figure 1.
(A) The “terpene” tab of the geosmin BGC of Streptomyces coelicolor A3(2) (NCBI ID NC_003888.3:6656219–6678399) with all details expanded. The product predictions cover both the geosmin precursor germacradienol and geosmin itself. (B) Tailoring functions identified in the balhimycin BGC of Amycolatopsis balhimycina (NCBI ID Y16952.3). The oxidoreductase category has been expanded to show that all four P450 monooxygenases were identified. OxyA–C are correctly annotated as having a cyclization function due to their similarity to the MITE entries of the corresponding cyclization enzymes from the vancomycin biosynthesis. In the transferases category, the bhaA halogenase entry has been expanded further to show the predictions based on the built-in halogenase prediction, MITE similarity, and smCoG-based gene function annotations.
See this image and copyright information in PMC

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