Metal–Ligand Interactions: Overlooked Confounders in Antibiotic Discovery and Development

The unabating rise of antimicrobial resistance makes the development of novel and effective antibiotics an urgent global health need. Progress toward assuaging this need is, however, limited by low levels of investment and patently low financial incentives. Eliminating inefficiencies in antibiotic development is therefore important to ensure effective deployment of limited resources. Metal interference in high-throughput assays, mechanism of action studies, and the eventual pharmacokinetics of antibiotics in development is an overlooked confounder in this process. In this Viewpoint, we, focusing on antibiotics, briefly provide a compartment-based approach to anticipating various possibilities for such interference and recommend toolkits for identification.

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Publication Details

Journal
ACS Infectious Diseases
Published
2026-03-11
DOI
https://doi.org/10.1021/acsinfecdis.6c00148
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

Metal–Ligand Interactions: Overlooked Confounders in Antibiotic Discovery and Development

Courtney C. Aldrich, Anthony D. Baughn, Ziyi Jia, Moyosore Oluseyi Orimoloye
ACS Infectious Diseases
Computational Drug Discovery Methods
article

Metal–Ligand Interactions: Overlooked Confounders in Antibiotic Discovery and Development

Courtney C. Aldrich, Anthony D. Baughn, Ziyi Jia, Moyosore Oluseyi Orimoloye
article en

Abstract

The unabating rise of antimicrobial resistance makes the development of novel and effective antibiotics an urgent global health need. Progress toward assuaging this need is, however, limited by low levels of investment and patently low financial incentives. Eliminating inefficiencies in antibiotic development is therefore important to ensure effective deployment of limited resources. Metal interference in high-throughput assays, mechanism of action studies, and the eventual pharmacokinetics of antibiotics in development is an overlooked confounder in this process. In this Viewpoint, we, focusing on antibiotics, briefly provide a compartment-based approach to anticipating various possibilities for such interference and recommend toolkits for identification.

ACS Infectious Diseases
University of Minnesota System (US)
Partnerships for the goals
Openalex Percentile: Top 24%
Computational Drug Discovery Methods
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