# Untargeted metabolomics for triaging of cytochrome b inhibitors during Chagas’ disease drug discovery

**Authors:** A. Kenneth MacLeod, Lindsay B. Tulloch, Michele Tinti, Darren Edwards, Susan Wyllie, Kevin D. Read

PMC · DOI: 10.1371/journal.pntd.0013917 · 2026-01-20

## TL;DR

Researchers developed a method using untargeted metabolomics to quickly identify and deprioritize compounds that target cytochrome b in drug discovery for Chagas' disease.

## Contribution

The study introduces a reliable and flexible metabolomic signature to triage cytochrome b inhibitors early in drug discovery for Chagas' disease.

## Key findings

- Untargeted metabolomic profiling using LC-MS can reliably identify compounds acting through cytochrome b.
- A signature of 79 metabolites differentially expressed by at least 2-fold (p < 0.05) was identified.
- Unsupervised multivariate analysis clearly separated cytochrome b inhibitors from other compounds.

## Abstract

Chagas’ disease, caused by infection with the protozoan parasite Trypanosoma cruzi, is a potentially fatal condition for which new treatments are urgently needed. Due to the lack of validated drug targets, phenotypic screening followed by target deconvolution is the dominant approach in Chagas’ disease drug discovery. However, as most phenotypic screening hits act through a small number of promiscuous targets, implementation of counter-screening methodology for these targets as early as possible in the workflow is essential to enable prioritisation of compounds with novel Modes of Action (MoA). Here, we demonstrate that untargeted metabolomic profiling using liquid chromatography mass spectrometry (LC-MS) can reliably identify compounds that act through one of the most common targets, cytochrome b. Treatment of epimastigote form T. cruzi in culture with cytochrome b inhibitors resulted in rapid and pronounced perturbation of the metabolome. We identified a signature of 79 metabolites that were differentially expressed by at least 2-fold (p < 0.05). Unsupervised multivariate analysis using these features allowed clear separation of cytochrome b inhibitors from compounds acting through other MoA, and through disruption of oxidative phosphorylation by other mechanisms. Flexibility was observed in this cytochrome b signature between experiments, and depending on the compounds used, suggesting that this approach could be readily implemented in other laboratories. Triage of cytochrome b inhibitors early in the Chagas’ disease drug discovery workflow using untargeted metabolomics will aid in prioritisation of medicinal chemistry resources towards compounds acting through novel mechanisms.

Chagas’ disease, a consequence of infection with the parasite Trypanosoma cruzi, is a severe global health problem. Most of the 6–7 million infected individuals reside in Latin America and increasing human migration is driving global dispersion. There are only two drugs available for treatment, both of which are poorly efficacious in the chronic phase of infection where progression to heart failure and sudden death is a frequent occurrence. New medicines that target novel aspects of parasite biology are urgently needed but most of the chemical start points identified in drug discovery projects are eventually found to act through similar mechanisms. Implementation of methodology to enable prioritisation of compounds with novel Modes of Action (MoA) as early as possible during drug discovery programmes is essential for the effective allocation of medicinal chemistry resource. To this end, we report here a MoA classification method which enables the identification and deprioritisation of compounds acting through one of the most common T. cruzi targets, cytochrome b, during Chagas disease drug discovery. The flexibility of this technique suggests that it could be readily implemented in other laboratories.

## Linked entities

- **Proteins:** Cytochrome B (cytochrome b)
- **Diseases:** Chagas’ disease (MONDO:0001444)
- **Species:** Trypanosoma cruzi (taxon 5693)

## Full-text entities

- **Diseases:** headache (MESH:D006261), deaths (MESH:D003643), heart failure (MESH:D006333), Malaria (MESH:D008288), leishmania (MESH:D007896), fever (MESH:D005334), Chagas disease (MESH:D014355), inflammation (MESH:D007249), digestive and cardiac disorders (MESH:D006331), infected (MESH:D007239), muscle pain (MESH:D063806), sudden death (MESH:D003645)
- **Chemicals:** phosphate (MESH:D010710), pyrimidine (MESH:C030986), CHCl3 (MESH:D002725), isovaleryl-CoA (MESH:C017447), sterol (MESH:D013261), EtOH (MESH:D000431), inosine monophosphate (MESH:D007291), oxygen (MESH:D010100), proton (MESH:D011522), AMP (MESH:D000249), aspartate (MESH:D001224), succinate (MESH:D019802), ATP (MESH:D000255), acetic acid (MESH:D019342), NAD + (MESH:D009243), PBS (MESH:D007854), phosphoarginine (MESH:C015441), proline (MESH:D011392), folate (MESH:D005492), nifurtimox (MESH:D009547), ammonium acetate (MESH:C018824), water (MESH:D014867), TCA (MESH:D014238), GTP (MESH:D006160), fumarate (MESH:D005650), ADP (MESH:D000244), Benznidazole (MESH:C009999), amino acids (MESH:D000596), resazurin (MESH:C005843), isovalerylcarnitine (MESH:C027333), glycolipid (MESH:D006017), 2,4-dinitrophenol (MESH:D019297), ETC (-), acetonitrile (MESH:C032159), chitin (MESH:D002686), oligomycin A (MESH:C031004), ubiquinol (MESH:C003741), Lactate (MESH:D019344), UQ (MESH:D014451)
- **Species:** Escherichia coli (E. coli, species) [taxon 562], Trypanosoma cruzi (species) [taxon 5693], Leishmania donovani (species) [taxon 5661], Plasmodium falciparum (malaria parasite P. falciparum, species) [taxon 5833], Mycolicibacterium smegmatis (species) [taxon 1772], Homo sapiens (human, species) [taxon 9606], Staphylococcus aureus (species) [taxon 1280]
- **Mutations:** H23 N, H37 N, H11 N, H27 N, H10 N, H13 N, H22 N, H14 N

## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12844530/full.md

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Source: https://tomesphere.com/paper/PMC12844530