Propagating annotations of molecular networks using in silico fragmentation

• Published in: PLoS computational biology Vol. 14; no. 4; p. e1006089
• Main Authors: da Silva, Ricardo R, Wang, Mingxun, Nothias, Louis-Félix, van der Hooft, Justin J J, Caraballo-Rodríguez, Andrés Mauricio, Fox, Evan, Balunas, Marcy J, Klassen, Jonathan L, Lopes, Norberto Peporine, Dorrestein, Pieter C
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.04.2018; Public Library of Science (PLoS)
• Subjects: Animals; Annotations; Ants - microbiology; Bioinformatica; Bioinformatics; Biology; Biology and Life Sciences; Biosynthesis; Cluster Analysis; Collaboration; Computational Biology; Computer and Information Sciences; Computer Simulation; Databases, Chemical; Euphorbia dendroides; Fragmentation; Fungi - chemistry; Fungi - isolation & purification; HyperText Markup Language; Hypotheses; Inspection; Internet; Mass spectrometry; Mass spectroscopy; Mathematical models; Metabolic Networks and Pathways; Metabolomics - methods; Metabolomics - statistics & numerical data; Models, Biological; Models, Chemical; Molecular dynamics; Molecular Structure; Networking; Pharmaceutical sciences; Pharmacy; Physical Sciences; Predictions; Propagation; Research and Analysis Methods; Scientific imaging; Servers; Software; Spectra; Spectroscopy; Tandem Mass Spectrometry - statistics & numerical data; Topology; Brazil; La Jolla California; California; United States > US
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006089

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.