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Dereplication of microbial metabolites through database search of mass spectra.
Mohimani, Hosein; Gurevich, Alexey; Shlemov, Alexander; Mikheenko, Alla; Korobeynikov, Anton; Cao, Liu; Shcherbin, Egor; Nothias, Louis-Felix; Dorrestein, Pieter C; Pevzner, Pavel A.
Afiliación
  • Mohimani H; Computational Biology Department, School of Computer Sciences, Carnegie Mellon University, Pittsburgh, PA, USA. hoseinm@andrew.cmu.edu.
  • Gurevich A; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA. hoseinm@andrew.cmu.edu.
  • Shlemov A; Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
  • Mikheenko A; Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
  • Korobeynikov A; Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
  • Cao L; Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
  • Shcherbin E; Department of Statistical Modelling, St. Petersburg State University, St. Petersburg, Russia.
  • Nothias LF; Computational Biology Department, School of Computer Sciences, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Dorrestein PC; National Research University Higher School of Economics, St. Petersburg, Russia.
  • Pevzner PA; Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
Nat Commun ; 9(1): 4035, 2018 10 02.
Article en En | MEDLINE | ID: mdl-30279420
ABSTRACT
Natural products have traditionally been rich sources for drug discovery. In order to clear the road toward the discovery of unknown natural products, biologists need dereplication strategies that identify known ones. Here we report DEREPLICATOR+, an algorithm that improves on the previous approaches for identifying peptidic natural products, and extends them for identification of polyketides, terpenes, benzenoids, alkaloids, flavonoids, and other classes of natural products. We show that DEREPLICATOR+ can search all spectra in the recently launched Global Natural Products Social molecular network and identify an order of magnitude more natural products than previous dereplication efforts. We further demonstrate that DEREPLICATOR+ enables cross-validation of genome-mining and peptidogenomics/glycogenomics results.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Espectrometría de Masas / Productos Biológicos / Descubrimiento de Drogas Tipo de estudio: Evaluation_studies Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Espectrometría de Masas / Productos Biológicos / Descubrimiento de Drogas Tipo de estudio: Evaluation_studies Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos
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