Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences. Author Michael Skinnider, Chad Johnston, Mathusan Gunabalasingam, Nishanth Merwin, Agata Kieliszek, Robyn MacLellan, Haoxin Li, Michael Ranieri, Andrew Webster, My Cao, Annabelle Pfeifle, Norman Spencer, Huy To, Dan Wallace, Chris Dejong, Nathan Magarvey Publication Year 2020 Type Journal Article Abstract Novel antibiotics are urgently needed to address the looming global crisis of antibiotic resistance. Historically, the primary source of clinically used antibiotics has been microbial secondary metabolism. Microbial genome sequencing has revealed a plethora of uncharacterized natural antibiotics that remain to be discovered. However, the isolation of these molecules is hindered by the challenge of linking sequence information to the chemical structures of the encoded molecules. Here, we present PRISM 4, a comprehensive platform for prediction of the chemical structures of genomically encoded antibiotics, including all classes of bacterial antibiotics currently in clinical use. The accuracy of chemical structure prediction enables the development of machine-learning methods to predict the likely biological activity of encoded molecules. We apply PRISM 4 to chart secondary metabolite biosynthesis in a collection of over 10,000 bacterial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded antibiotics. PRISM 4 is freely available as an interactive web application at http://prism.adapsyn.com . Journal Nature communications Volume 11 Issue 1 Pages 6058 Date Published 11/2020 ISSN Number 2041-1723 DOI 10.1038/s41467-020-19986-1 Alternate Journal Nat Commun PMCID PMC7699628 PMID 33247171 PubMedPubMed CentralGoogle ScholarBibTeXEndNote X3 XML