Propagating annotations of molecular networks using < i > in silico < /i > fragmentation

by Ricardo R. da Silva, Mingxun Wang, Louis-F élix Nothias, Justin J. J. van der Hooft, Andrés Mauricio Caraballo-Rodríguez, Evan Fox, Marcy J. Balunas, Jonathan L. Klassen, Norberto Peporine Lopes, Pieter C. Dorrestein 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 ta ndem 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 appr oaches used to annotate an unknown fragmentation mass spectrum is through the use ofin silico predictions. One of the challenges ofin 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 ofin 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 improvein silico annotations. The Network Annotation Propagation...
Source: PLoS Computational Biology - Category: Biology Authors: Source Type: research