ArticleJournal of industrial microbiology & biotechnology2019
Sequence-based classification of type II polyketide synthase biosynthetic gene clusters for antiSMASH.
Article in Journal of industrial microbiology & biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 25 citations in OpenAlex.
- Sustainable Biocatalytic Cascades: A Versatile Tool in the Synthesis of Natural Products With Therapeutic Potential.Chembiochem : a European journal of chemical biology · 2026Review
- Article
- Strategies to decipher silent biosynthetic gene clusters in actinomycetes.Archives of microbiology · 2025Review
- High-Throughput Mining of Novel Compounds from Known Microbes: A Boost to Natural Product Screening.Molecules (Basel, Switzerland) · 2024Review
- Unveiling Microbial Chemical Interactions Based on Metabolomics Approaches.Advances in experimental medicine and biology · 2023Article
- Characterization of siderophores from Escherichia coli strains through genome mining tools: an antiSMASH study.AMB Express · 2022Article
- Strategies to access biosynthetic novelty in bacterial genomes for drug discovery.Nature reviews. Drug discovery · 2022Review
- Programmable polyketide biosynthesis platform for production of aromatic compounds in yeast.Synthetic and systems biotechnology · 2020Article
- antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline.Nucleic acids research · 2019Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
The software antiSMASH examines microbial genome data to identify and analyze biosynthetic gene clusters for a wide range of natural products. So far, type II polyketide synthase (PKS) gene clusters could only be identified, but no detailed predictions for type II PKS gene clusters could be provided. In this study, an antiSMASH module for analyzing type II PKS gene clusters has been developed. The module detects genes/proteins in the type II PKS gene cluster involved with polyketide biosynthesis and is able to make predictions about the aromatic polyketide product. Predictions include the putative starter unit, the number of malonyl elongations during polyketide biosynthesis, the putative class and the molecular weight of the product. Furthermore, putative cyclization patterns are predicted. The accuracy of the predictions generated with the new PKSII antiSMASH module was evaluated using a leave-one-out cross validation. The prediction module is available in antiSMASH version 5 at https://antismash.secondarymetabolites.org .
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