Norine: update of the nonribosomal peptide resource.

Norine, the unique resource dedicated to nonribosomal peptides (NRPs), is now updated with a new pipeline to automate massive sourcing and enhance annotation. External databases are mined to extract NRPs that are not yet in Norine. To maintain a high data quality, successive filters are applied to automatically validate the NRP annotations and only validated data is inserted in the database. External databases were also used to complete annotations of NRPs already in Norine. Besides, annotation consistency inside Norine and between Norine and external sources have reported annotation errors. Some can be corrected automatically, while others need manual curation. This new approach led to the insertion of 539 new NRPs and the addition or correction of annotations of nearly all Norine entries. Two new tools to analyse the chemical structures of NRPs (rBAN) and to infer a molecular formula from the mass-to-charge ratio of an NRP (Kendrick Formula Predictor) were also integrated. Norine is freely accessible from the following URL: https://bioinfo.cristal.univ-lille.fr/norine/.

Norine, the knowledgebase dedicated to non-ribosomal peptides, is now open to crowdsourcing.

Since its creation in 2006, Norine remains the unique knowledgebase dedicated to non-ribosomal peptides (NRPs). These secondary metabolites, produced by bacteria and fungi, harbor diverse interesting biological activities (such as antibiotic, antitumor, siderophore or surfactant) directly related to the diversity of their structures. The Norine team goal is to collect the NRPs and provide tools to analyze them efficiently. We have developed a user-friendly interface and dedicated tools to provide a complete bioinformatics platform. The knowledgebase gathers abundant and valuable annotations on more than 1100 NRPs. To increase the quantity of described NRPs and improve the quality of associated annotations, we are now opening Norine to crowdsourcing. We believe that contributors from the scientific community are the best experts to annotate the NRPs they work on. We have developed MyNorine to facilitate the submission of new NRPs or modifications of stored ones. This article presents MyNorine and other novelties of Norine interface released since the first publication. Norine is freely accessible from the following URL: http://bioinfo.lifl.fr/NRP.

Norine: Bioinformatics Methods and Tools for the Characterization of Newly Discovered Nonribosomal Peptides.

In this chapter, we present Norine ( https://norine.univ-lille.fr/norine ), the unique resource dedicated to nonribosomal peptides. First, the content of the knowledgebase and the related tools are described. Then, a study case shows how to query Norine by annotations or structure and how to interpret the obtained results.

rBAN: retro-biosynthetic analysis of nonribosomal peptides.

Proteinogenic and non-proteinogenic amino acids, fatty acids or glycans are some of the main building blocks of nonribsosomal peptides (NRPs) and as such may give insight into the origin, biosynthesis and bioactivities of their constitutive peptides. Hence, the structural representation of NRPs using monomers provides a biologically interesting skeleton of these secondary metabolites. Databases dedicated to NRPs such as Norine, already integrate monomer-based annotations in order to facilitate the development of structural analysis tools. In this paper, we present rBAN (retro-biosynthetic analysis of nonribosomal peptides), a new computational tool designed to predict the monomeric graph of NRPs from their atomic structure in SMILES format. This prediction is achieved through the "in silico" fragmentation of a chemical structure and matching the resulting fragments against the monomers of Norine for identification. Structures containing monomers not yet recorded in Norine, are processed in a "discovery mode" that uses the RESTful service from PubChem to search the unidentified substructures and suggest new monomers. rBAN was integrated in a pipeline for the curation of Norine data in which it was used to check the correspondence between the monomeric graphs annotated in Norine and SMILES-predicted graphs. The process concluded with the validation of the 97.26% of the records in Norine, a two-fold extension of its SMILES data and the introduction of 11 new monomers suggested in the discovery mode. The accuracy, robustness and high-performance of rBAN were demonstrated in benchmarking it against other tools with the same functionality: Smiles2Monomers and GRAPE.