Journal
NUCLEIC ACIDS RESEARCH
Volume 45, Issue W1, Pages W36-W41Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkx319
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Funding
- Novo Nordisk Foundation
- Netherlands Organization for Scientific Research (NWO) VENI Grant [863.15.002]
- Graduate School for Experimental Plant Sciences (EPS)
- Ministry of Science, ICT and Future Planning through the National Research Foundation (NRF) of Korea [NRF-2012M1A2A2026556]
- International Leibniz Research School for Microbial and Molecular Interactions (ILRS), as part of the excellence graduate school Jena School for Microbial Communication (JSMC)
- Deutsche Forschungsgemeinschaft (DFG)
- Collaborative Research Centre ChemBioSys by DFG [CRC 1127 ChemBioSys]
- NIH National Research Service Award [T32GM008505]
- David and Lucile Packard Fellowship for Science and Engineering
- Department of Chemistry at the University of Illinois at Urbana-Champaign Fellowship
- NIH Chemical Biology Interface Training Program Fellowship [T32 GM070421]
- Google Summer of Code grant
- Warwick Integrative Synthetic Biology Centre (WISB)
- Manchester Synthetic Biology Research Centre (SYNBIOCHEM) under the UK Research Councils' 'Synthetic Biology for Growth' programme [BB/M017982/1, BB/M017702/1]
- Netherlands Organization for Scientific Research (NWO)
- BBSRC [BB/M017702/1] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/M017702/1] Funding Source: researchfish
- NNF Center for Biosustainability [New Bioactive Compounds] Funding Source: researchfish
- Novo Nordisk Fonden [NNF16OC0021746, NNF10CC1016517] Funding Source: researchfish
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Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CAS-SIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.
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