antiSMASH 6.0 improves cluster detection and comparison capabilities. It supports 71 cluster types, compared to 58 in version 5. It displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, and allows integration of results from other prediction tools. It also improves detection of tailoring enzymes in RiPP clusters. antiSMASH uses rule-based approaches to identify biosynthetic pathways. It has been widely used for detecting and characterizing BGCs in bacteria and fungi. It is considered the gold standard for this task. antiSMASH 6 includes new rules for RiPPs, including splitting the lanthipeptide rule into individual classes. It also adds support for BGCs producing thioamide-containing non-ribosomal peptides, tropodithiic acid, Serratia-type prodigiosins, non-alpha poly-amino acids, and pyrrolidines. It detects and displays modules in multi-modular enzymes, improving prediction of biosynthetic modifications. It also includes a new ClusterCompare algorithm that uses protein sequence comparisons, gene synteny, and biosynthetic component presence/absence for more accurate comparisons. antiSMASH 6 also supports sideloading, allowing external tools to annotate additional regions and clusters. It improves annotation for RiPP clusters by integrating RRE-Finder to identify tailoring enzymes. It also includes optimizations for PFAM and TIGRFAM analysis. antiSMASH 6 is available as a web server and standalone tool, with source code available on GitHub. Funding was provided by the Novo Nordisk Foundation and other organizations. antiSMASH is used in various databases and tools for genome mining and analysis. It is an open-source tool that integrates well with other computational tools in the natural products field. Future updates will improve predictions of chemical structures of compounds produced by BGCs, linking them to metabolomics data and databases like GNPS.antiSMASH 6.0 improves cluster detection and comparison capabilities. It supports 71 cluster types, compared to 58 in version 5. It displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, and allows integration of results from other prediction tools. It also improves detection of tailoring enzymes in RiPP clusters. antiSMASH uses rule-based approaches to identify biosynthetic pathways. It has been widely used for detecting and characterizing BGCs in bacteria and fungi. It is considered the gold standard for this task. antiSMASH 6 includes new rules for RiPPs, including splitting the lanthipeptide rule into individual classes. It also adds support for BGCs producing thioamide-containing non-ribosomal peptides, tropodithiic acid, Serratia-type prodigiosins, non-alpha poly-amino acids, and pyrrolidines. It detects and displays modules in multi-modular enzymes, improving prediction of biosynthetic modifications. It also includes a new ClusterCompare algorithm that uses protein sequence comparisons, gene synteny, and biosynthetic component presence/absence for more accurate comparisons. antiSMASH 6 also supports sideloading, allowing external tools to annotate additional regions and clusters. It improves annotation for RiPP clusters by integrating RRE-Finder to identify tailoring enzymes. It also includes optimizations for PFAM and TIGRFAM analysis. antiSMASH 6 is available as a web server and standalone tool, with source code available on GitHub. Funding was provided by the Novo Nordisk Foundation and other organizations. antiSMASH is used in various databases and tools for genome mining and analysis. It is an open-source tool that integrates well with other computational tools in the natural products field. Future updates will improve predictions of chemical structures of compounds produced by BGCs, linking them to metabolomics data and databases like GNPS.