ArticleJournal of medicinal chemistry2022
Data-Driven Derivation of Molecular Substructures That Enhance Drug Activity in Gram-Negative Bacteria.
Article in Journal of medicinal chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Development of Pyrimido Pyridazine Analogs through Increased Whole Cell Target Engagement of the Dihydropteroate Synthase Pterin Binding Site in Gram-Negative Bacteria.ACS infectious diseases · 2025Article
- Measurement and prediction of small molecule retention by Gram-negative bacteria based on a large-scale LC/MS screen.Scientific reports · 2025Article
- Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning.Journal of chemical information and modeling · 2025Article
- Multidrug efflux in Gram-negative bacteria: structural modifications in active compounds leading to efflux pump avoidance.npj antimicrobials and resistance · 2024Article
- Guiding the Way: Traditional Medicinal Chemistry Inspiration for Rational Gram-Negative Drug Design.Journal of medicinal chemistry · 2024Review
- Artificial intelligence applications in the diagnosis and treatment of bacterial infections.Frontiers in microbiology · 2024Review
- Small-Molecule Antibiotic Drug Development: Need and Challenges.ACS infectious diseases · 2023Review
- Fast prediction of antibiotic permeability through membrane channels using Brownian dynamics.Biophysical journal · 2023Article
- Challenges and shortcomings of antibacterial discovery projects.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The complex cell envelope of Gram-negative bacteria creates a formidable barrier to antibiotic influx. Reduced drug uptake impedes drug development and contributes to a wide range of drug-resistant bacterial infections, including those caused by extremely resistant species prioritized by the World Health Organization. To develop new and efficient treatments, a better understanding of the molecular features governing Gram-negative permeability is essential. Here, we present a data-driven approach, using matched molecular pair analysis and machine learning on minimal inhibitory concentration data from Gram-positive and Gram-negative bacteria to uncover chemical features that influence Gram-negative bioactivity. We find recurring chemical moieties, of a wider range than previously known, that consistently improve activity and suggest that this insight can be used to optimize compounds for increased Gram-negative uptake. Our findings may help to expand the chemical space of broad-spectrum antibiotics and aid the search for new antibiotic compound classes.
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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.