ReviewCurrent opinion in microbiology2026
Harnessing artificial intelligence for antimicrobial discovery and optimization.
Review in Current opinion in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The rise of antimicrobial-resistant pathogens has outpaced the traditional methods of drug discovery and development, emphasizing a need for new and innovative approaches to identifying novel antibiotics. Artificial intelligence (AI) poses new opportunities to overcome the challenges in traditional drug discovery by accelerating the identification, design, and optimization of bioactive small molecules and antimicrobial peptides. AI-driven genome mining allows for the identification and prioritization of biosynthetic gene clusters, while advanced AI models facilitate molecular property prediction, predicted binding interactions, and novel structure design. This review explores the advancements that AI has enabled in antimicrobial discovery and design, as well as its current limitations.
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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.