Paper Info
Title
Nrpspredictor2-A Web Server For Predicting Nrps Adenylation Domain Specificity
Abstract
The products of many bacterial non-ribosomal peptide synthetases (NRPS) are highly important secondary metabolites, including vancomycin and other antibiotics. The ability to predict substrate specificity of newly detected NRPS Adenylation (A-) domains by genome sequencing efforts is of great importance to identify and annotate new gene clusters that produce secondary metabolites. Prediction of A-domain specificity based on the sequence alone can be achieved through sequence signatures or, more accurately, through machine learning methods. We present an improved predictor, based on previous work (NRPSpredictor), that predicts A-domain specificity using Support Vector Machines on four hierarchical levels, ranging from gross physicochemical properties of an A-domain's substrates down to single amino acid substrates. The three more general levels are predicted with an F-measure better than 0.89 and the most detailed level with an average F-measure of 0.80. We also modeled the applicability domain of our predictor to estimate for new A-domains whether they lie in the applicability domain. Finally, since there are also NRPS that play an important role in natural products chemistry of fungi, such as peptaibols and cephalosporins, we added a predictor for fungal A-domains, which predicts gross physicochemical properties with an F-measure of 0.84. The service is available at http://nrps.informatik.uni-tuebingen.de/.
Year
DOI
Venue
2011
10.1093/nar/gkr323
NUCLEIC ACIDS RESEARCH
Field
DocType
Volume
Gene cluster,Adenylylation,Gene,Domain specificity,Biology,DNA sequencing,Genetics,Applicability domain,Peptide Synthetases,Web server
Journal
39
Issue
ISSN
Citations 
Web Server issue
0305-1048
12
PageRank 
References 
Authors
1.15
10
6
Name
Order
Citations
PageRank
Marc Röttig1252.99
Marnix H Medema28012.12
Kai Blin3588.33
Tilmann Weber4537.49
Christian Rausch5865.37
Oliver Kohlbacher6975101.91