Blin, Kai, Wolf, Thomas, Chevrette, Marc G., Lu, Xiaowen, Schwalen, Christopher J., Kautsar, Satria A., Suarez Duran, Hernando G., Emmanuel de los Santos, L. C., Kim, Hyun Uk, Nave, Mariana, Dickschat, Jeroen S., Mitchell, Douglas A., Shelest, Ekaterina, Breitling, Rainer, Takano, Eriko, Lee, Sang Yup, Weber, Tilmann and Medema, Marnix H. (2017) antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Research . doi:10.1093/nar/gkx319 ISSN 0305-1048.

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Abstract

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 CASSIS 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.

Item Type:	Journal Article
Subjects:	Q Science > QH Natural history > QH426 Genetics
Divisions:	Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Library of Congress Subject Headings (LCSH):	Genomics -- Technique -- Computer programs , Peptides, Polyketides
Journal or Publication Title:	Nucleic Acids Research
Publisher:	Oxford University Press
ISSN:	0305-1048
Official Date:	28 April 2017
Dates:	Date Event 28 April 2017 Published 13 April 2017 Accepted
DOI:	10.1093/nar/gkx319
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	3 May 2017
Date of first compliant Open Access:	8 May 2017
Funder:	Novo Nordisk Foundation, Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Netherlands Organisation for Scientific Research] (NWO), Netherlands. Graduate School Experimental Plant Sciences (EPS), National Research Foundation of Korea (NRF), Deutsche Forschungsgemeinschaft (DFG), National Institutes of Health (U.S.) (NIH), University of Illinois (Urbana-Champaign campus). Department of Chemistry, Google (Firm), University of Warwick. Integrative Synthetic Biology Centre, University of Manchester. Manchester Centre for Integrative Systems Biology (MCISB), Research Councils UK (RCUK)
Grant number:	863.15.00 (NWO), 2012M1A2A202655 (NRF), CRC1127 ChemBioSys (DFG), T32GM008505, T32GM070421 (NIH), BB/M017982/ 1WISB, BB/M017702/1 SYN- BIOCHEM, (RCUK)

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