The article introduces the updated version 6 of antiSMASH, a widely used tool for detecting and characterizing biosynthetic gene clusters (BGCs) in bacteria and fungi. Key improvements in antiSMASH 6 include: 1. **Increased Cluster Types**: The number of supported cluster types has been expanded from 58 to 71, with a focus on ribosomally synthesized and post-translationally modified peptides (RiPPs). 2. **Module Detection**: Enhanced detection and display of modular structures in multi-modular BGCs, such as non-ribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), to better predict modifications during biosynthesis. 3. **ClusterCompare**: Introduction of a new cluster comparison algorithm that uses gene synteny and the presence/absence of biosynthetic components to provide more accurate and robust comparisons. 4. **Sideload Functionality**: Improved interoperability with other gene cluster annotation tools through a JSON-based file format, allowing for the integration of additional regions and clusters. 5. **RiPP Cluster Annotation**: Integration of RRE-Finder to more confidently identify tailoring enzymes in RiPP clusters, enhancing the detection of novel RiPP clusters. 6. **Database Updates**: The antiSMASH database has been refreshed to include high-quality BGC regions from archaeal, bacterial, and fungal genomes, improving the relevance of hits for users with diverse input data. These updates position antiSMASH as a leading tool for microbial genome mining, integrating well with the broader ecosystem of computational tools in the natural products field. Future updates aim to further improve the chemical structure predictions of compounds produced by detected BGCs, facilitating connections between gene clusters and identified metabolites.The article introduces the updated version 6 of antiSMASH, a widely used tool for detecting and characterizing biosynthetic gene clusters (BGCs) in bacteria and fungi. Key improvements in antiSMASH 6 include: 1. **Increased Cluster Types**: The number of supported cluster types has been expanded from 58 to 71, with a focus on ribosomally synthesized and post-translationally modified peptides (RiPPs). 2. **Module Detection**: Enhanced detection and display of modular structures in multi-modular BGCs, such as non-ribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), to better predict modifications during biosynthesis. 3. **ClusterCompare**: Introduction of a new cluster comparison algorithm that uses gene synteny and the presence/absence of biosynthetic components to provide more accurate and robust comparisons. 4. **Sideload Functionality**: Improved interoperability with other gene cluster annotation tools through a JSON-based file format, allowing for the integration of additional regions and clusters. 5. **RiPP Cluster Annotation**: Integration of RRE-Finder to more confidently identify tailoring enzymes in RiPP clusters, enhancing the detection of novel RiPP clusters. 6. **Database Updates**: The antiSMASH database has been refreshed to include high-quality BGC regions from archaeal, bacterial, and fungal genomes, improving the relevance of hits for users with diverse input data. These updates position antiSMASH as a leading tool for microbial genome mining, integrating well with the broader ecosystem of computational tools in the natural products field. Future updates aim to further improve the chemical structure predictions of compounds produced by detected BGCs, facilitating connections between gene clusters and identified metabolites.