Title
Antismash 3.0-A Comprehensive Resource For The Genome Mining Of Biosynthetic Gene Clusters
Abstract
Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and standalone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated patternmatching procedure and Enzyme Commission numbers are assigned to functionally classify all enzymecoding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.
Year
DOI
Venue
2015
10.1093/nar/gkv437
NUCLEIC ACIDS RESEARCH
Field
DocType
Volume
Gene cluster,Genome,ENCODE,Gene,Biology,Polyketide,Genomics,Genetics,Putative gene,Web server
Journal
43
Issue
ISSN
Citations 
W1
0305-1048
21
PageRank 
References 
Authors
1.39
11
13
Name
Order
Citations
PageRank
Tilmann Weber1211.39
Kai Blin2322.00
Srikanth Duddela3211.39
Daniel Krug4211.39
Hyun Uk Kim5232.11
Robert Bruccoleri6211.39
Sang Yup Lee720719.79
Michael A Fischbach8211.39
R Müller9787.04
Wolfgang Wohlleben10211.39
Rainer Breitling1166347.19
Eriko Takano12211.39
Marnix H Medema138012.12