ArticleNature communications2023
Empowering drug off-target discovery with metabolic and structural analysis.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Machine Learning-Integrated Metabolomics for Precision Pharmacotherapy: Advances, Challenges, and Clinical Translation.Metabolites · 2026Review
- Amino acid homeostasis in the kidney: Physiological roles and pathological dysregulation.Physiological reports · 2026Review
- When Side Effects Become Therapies: A Mechanistic Taxonomy of Adverse Drug Reactions as Translational Signals for Drug Repositioning.Fundamental & clinical pharmacology · 2026Review
- Co-targeting Metabolic Neighbours Constraints Bacterial Adaptive Evolution.bioRxiv : the preprint server for biology · 2026Article
- Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics.bioRxiv : the preprint server for biology · 2026Article
- Review
- Therapeutic target database 2026: facilitating targeted therapies and precision medicine.Nucleic acids research · 2026Article
- Metabolomics and Pharmacometabolomics: Advancing Precision Medicine in Drug Discovery and Development.Metabolites · 2025Review
- Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Identification of Ribonuclease Inhibitors for the Control of Pathogenic Bacteria.International journal of molecular sciences · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic workflow to focus on specific targets based on analysis of metabolomics data and growth rescue experiments. We deploy this framework to understand the intracellular molecular interactions of the multi-valent dihydrofolate reductase-targeting antibiotic compound CD15-3. We analyse global metabolomics data utilizing machine learning, metabolic modelling, and protein structural similarity to prioritize candidate drug targets. Overexpression and in vitro activity assays confirm one of the predicted candidates, HPPK (folK), as a CD15-3 off-target. This study demonstrates how established machine learning methods can be combined with mechanistic analyses to improve the resolution of drug target finding workflows for discovering off-targets of a metabolic inhibitor.
Indexed as
Identifiers
What OpenQuestion holds
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.