ArticleMetabolites2020
Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics.
Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 26 citations in OpenAlex.
- Molecular Structure Discovery for Untargeted Metabolomics Using Biotransformation Rules and Global Molecular Networking.Analytical chemistry · 2025Article
- Computational analysis of the gut microbiota-mediated drug metabolism.Computational and structural biotechnology journal · 2025Article
- An Ensemble Spectral Prediction (ESP) model for metabolite annotation.Bioinformatics (Oxford, England) · 2024Article
- Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota.NPJ systems biology and applications · 2024Article
- Article
- Recent advances in mass spectrometry-based computational metabolomics.Current opinion in chemical biology · 2023Review
- Pickaxe: a Python library for the prediction of novel metabolic reactions.BMC bioinformatics · 2023Article
- MINE 2.0: enhanced biochemical coverage for peak identification in untargeted metabolomics.Bioinformatics (Oxford, England) · 2022Article
- Approaches for completing metabolic networks through metabolite damage and repair discovery.Current opinion in systems biology · 2021Review
- MassGenie: A Transformer-Based Deep Learning Method for Identifying Small Molecules from Their Mass Spectra.Biomolecules · 2021Article
- Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification.Bioinformatics (Oxford, England) · 2021Article
- Analysis of metabolic network disruption in engineered microbial hosts due to enzyme promiscuity.Metabolic engineering communications · 2021Article
- Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics-Standardization, Coverage, and Throughput.Analytical chemistry · 2021Review
- Pathway-Activity Likelihood Analysis and Metabolite Annotation for Untargeted Metabolomics Using Probabilistic Modeling.Metabolites · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Mass spectrometry coupled with chromatography separation techniques provides a powerful platform for untargeted metabolomics. Determining the chemical identities of detected compounds however remains a major challenge. Here, we present a novel computational workflow, termed extended metabolic model filtering (EMMF), that aims to engineer a candidate set, a listing of putative chemical identities to be used during annotation, through an extended metabolic model (EMM). An EMM includes not only canonical substrates and products of enzymes already cataloged in a database through a reference metabolic model, but also metabolites that can form due to substrate promiscuity. EMMF aims to strike a balance between discovering previously uncharacterized metabolites and the computational burden of annotation. EMMF was applied to untargeted LC-MS data collected from cultures of Chinese hamster ovary (CHO) cells and murine cecal microbiota. EMM metabolites matched, on average, to 23.92% of measured masses, providing a > 7-fold increase in the candidate set size when compared to a reference metabolic model. Many metabolites suggested by EMMF are not catalogued in PubChem. For the CHO cell, we experimentally confirmed the presence of 4-hydroxyphenyllactate, a metabolite predicted by EMMF that has not been previously documented as part of the CHO cell metabolic model.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.