Result: Improving annotation propagation on molecular networks through random walks: introducing ChemWalker.

Title:
Improving annotation propagation on molecular networks through random walks: introducing ChemWalker.
Authors:
Borelli TC; NPPNS, Department of Molecular Biosciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP 14040-903, Brazil., Arini GS; NPPNS, Department of Molecular Biosciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP 14040-903, Brazil., Feitosa LGP; NPPNS, Department of Molecular Biosciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP 14040-903, Brazil., Dorrestein PC; Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA 92093, USA., Lopes NP; NPPNS, Department of Molecular Biosciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP 14040-903, Brazil., da Silva RR; NPPNS, Department of Molecular Biosciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP 14040-903, Brazil.
Source:
Bioinformatics (Oxford, England) [Bioinformatics] 2023 Mar 01; Vol. 39 (3).
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: Oxford : Oxford University Press, c1998-
MeSH Terms:
Libraries*, Databases, Factual ; Gene Library ; Mass Spectrometry ; Probability
Comments:
Erratum in: Bioinformatics. 2023 Mar 1;39(3):btad147. doi: 10.1093/bioinformatics/btad147. (PMID: 36961962)
References:
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Nat Biotechnol. 2016 Aug 9;34(8):828-837. (PMID: 27504778)
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Front Plant Sci. 2019 Jul 02;10:846. (PMID: 31333695)
Nat Biotechnol. 2022 Mar;40(3):411-421. (PMID: 34650271)
PLoS Comput Biol. 2018 Apr 18;14(4):e1006089. (PMID: 29668671)
Grant Information:
2021/08235-3 São Paulo Research Foundation
Entry Date(s):
Date Created: 20230303 Date Completed: 20230309 Latest Revision: 20230328
Update Code:
20250114
PubMed Central ID:
PMC9991053
DOI:
10.1093/bioinformatics/btad078
PMID:
36864626
Database:
MEDLINE

Further Information

Motivation: Annotation of the mass signals is still the biggest bottleneck for the untargeted mass spectrometry analysis of complex mixtures. Molecular networks are being increasingly adopted by the mass spectrometry community as a tool to annotate large-scale experiments. We have previously shown that the process of propagating annotations from spectral library matches on molecular networks can be automated using Network Annotation Propagation (NAP). One of the limitations of NAP is that the information for the spectral matches is only propagated locally, to the first neighbor of a spectral match. Here, we show that annotation propagation can be expanded to nodes not directly connected to spectral matches using random walks on graphs, introducing the ChemWalker python library.
Results: Similarly to NAP, ChemWalker relies on combinatorial in silico fragmentation results, performed by MetFrag, searching biologically relevant databases. Departing from the combination of a spectral network and the structural similarity among candidate structures, we have used MetFusion Scoring function to create a weight function, producing a weighted graph. This graph was subsequently used by the random walk to calculate the probability of 'walking' through a set of candidates, departing from seed nodes (represented by spectral library matches). This approach allowed the information propagation to nodes not directly connected to the spectral library match. Compared with NAP, ChemWalker has a series of improvements, on running time, scalability and maintainability and is available as a standalone python package.
Availability and Implementation: ChemWalker is freely available at https://github.com/computational-chemical-biology/ChemWalker.
Contact: ridasilva@usp.br.
Supplementary Information: Supplementary data are available at Bioinformatics online.
(© The Author(s) 2023. Published by Oxford University Press.)