ArticleJournal of chemical information and modeling2020
Machine Learning Algorithm Identifies an Antibiotic Vocabulary for Permeating Gram-Negative Bacteria.
Article in Journal of chemical information and modeling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Antimicrobial resistance crisis: could artificial intelligence be the solution?Military Medical Research · 2024Pooled it
- Random Forest Modeling to Predict Small Molecule Accumulation in Gram-Negative Bacteria.ACS infectious diseases · 2026Article
- Improving Generalizability in Whole-Cell Antibiotic Discovery Through Active Learning.bioRxiv : the preprint server for biology · 2026Article
- The Quantification of Drug Accumulation within Gram-Negative Bacteria.ACS infectious diseases · 2026Article
- AI-Driven Innovations in Hearing Health: A Review of Artificial Intelligence Applications in Audiology and Hearing Technologies.Current aging science · 2026Review
- Artificial Intelligence in Selected Domains of Drug Discovery: A Critical Narrative Review.Drug design, development and therapy · 2026Review
- Sophisticated natural products as antibiotics.Nature · 2024Review
- Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors.Communications chemistry · 2024Article
- Diagnosis, Treatment, and Management of Otitis Media with Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2023Review
- New understanding of multidrug efflux and permeation in antibiotic resistance, persistence, and heteroresistance.Annals of the New York Academy of Sciences · 2023Review
- Article
- Property space mapping of Pseudomonas aeruginosa permeability to small molecules.Scientific reports · 2022Article
- Data-Driven Derivation of Molecular Substructures That Enhance Drug Activity in Gram-Negative Bacteria.Journal of medicinal chemistry · 2022Article
- Machine Learning in Antibacterial Drug Design.Frontiers in pharmacology · 2022Review
- β-Lactam potentiators to re-sensitize resistant pathogens: Discovery, development, clinical use and the way forward.Frontiers in microbiology · 2022Review
- Artificial Intelligence and Antibiotic Discovery.Antibiotics (Basel, Switzerland) · 2021Review
- Challenges in Drug Discovery for Intracellular Bacteria.Pathogens (Basel, Switzerland) · 2021Article
- Accelerating antibiotic discovery through artificial intelligence.Communications biology · 2021Review
- Outer membrane permeability: Antimicrobials and diverse nutrients bypass porins inProceedings of the National Academy of Sciences of the United States of America · 2021Article
- The Whole Is Bigger than the Sum of Its Parts: Drug Transport in the Context of Two Membranes with Active Efflux.Chemical reviews · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Drug discovery faces a crisis. The industry has used up the "obvious" space in which to find novel drugs for biomedical applications, and productivity is declining. One strategy to combat this is rational approaches to expand the search space without relying on chemical intuition, to avoid rediscovery of similar spaces. In this work, we present proof of concept of an approach to rationally identify a "chemical vocabulary" related to a specific drug activity of interest without employing known rules. We focus on the pressing concern of multidrug resistance in
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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.