ArticleNature2017
Predictive compound accumulation rules yield a broad-spectrum antibiotic.
Article in Nature, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 427 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
427 citing papers in PubMed, 861 citations in OpenAlex.
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- Random Forest Modeling to Predict Small Molecule Accumulation in Gram-Negative Bacteria.ACS infectious diseases · 2026Article
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- Deep-learning-based virtual screening of antibacterial compounds.Nature biotechnology · 2026Article
- Chemical inhibition of a CBASS anti-bacteriophage defense.iScience · 2026Article
- A Siderophore-Antibiotic Heterodimer Imaging Agent EnablesJournal of medicinal chemistry · 2026Article
- Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets.bioRxiv : the preprint server for biology · 2026Article
- Co-targeting Metabolic Neighbours Constraints Bacterial Adaptive Evolution.bioRxiv : the preprint server for biology · 2026Article
- Integrating machine learning and artificial intelligence in the management of Acinetobacter infections: a narrative review.Infection · 2026Review
- Structure-Activity Relationship Studies for 1,3,4-Thiadiazole-Based Bacterial Carbonic Anhydrase Inhibitors withJournal of medicinal chemistry · 2026Article
367 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Most small molecules are unable to rapidly traverse the outer membrane of Gram-negative bacteria and accumulate inside these cells, making the discovery of much-needed drugs against these pathogens challenging. Current understanding of the physicochemical properties that dictate small-molecule accumulation in Gram-negative bacteria is largely based on retrospective analyses of antibacterial agents, which suggest that polarity and molecular weight are key factors. Here we assess the ability of over 180 diverse compounds to accumulate in Escherichia coli. Computational analysis of the results reveals major differences from the retrospective studies, namely that the small molecules that are most likely to accumulate contain an amine, are amphiphilic and rigid, and have low globularity. These guidelines were then applied to convert deoxynybomycin, a natural product that is active only against Gram-positive organisms, into an antibiotic with activity against a diverse panel of multi-drug-resistant Gram-negative pathogens. We anticipate that these findings will aid in the discovery and development of antibiotics against Gram-negative bacteria.
Indexed as
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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.