{"schemaVersion":"1.0","generatedFrom":"https://brightaifuture.com/discoveries/mrsa","record":{"id":"mrsa","headline":"Looking for new antibiotic families.","canonicalUrl":"https://brightaifuture.com/discoveries/mrsa","datePublished":"2026-09-05","dateModified":null,"sourcePublicationDate":"2023-12-20","author":null,"publisher":{"name":"Bright AI Future","url":"https://brightaifuture.com/"},"topics":["biology"],"summary":"Researchers used explainable deep learning to identify a structural class of antibiotic candidates.","evidenceState":"Experimental","keyFacts":[{"label":"AI’s role","value":"Models predicted activity and highlighted chemical substructures."},{"label":"Documented result","value":"Candidate compounds showed antibacterial activity, including tests in mouse models."},{"label":"Important limitation","value":"Preclinical findings do not demonstrate human safety or effectiveness."}],"limitations":["Preclinical findings do not demonstrate human safety or effectiveness."],"evidenceLinks":[{"title":"Discovery of a structural class of antibiotics with explainable deep learning","url":"https://www.nature.com/articles/s41586-023-06887-8","type":"paper"}],"evidencePackUrl":"https://brightaifuture.com/evidence-pack/mrsa","embedUrl":"https://brightaifuture.com/embed/story/mrsa","attribution":{"credit":"Bright AI Future","requirements":["Link to the canonical Bright record.","Keep material limitations with the claim they qualify.","Link to the original evidence when repeating a substantive claim.","Do not describe a source check or organization-reported result as independent verification."],"sourceRights":"Linked source material, quotations, trademarks and media remain subject to their owners’ terms. No reuse right is granted for third-party media."}},"claim":{"humanProblem":"Drug resistance creates demand for new classes of antibiotics.","priorConstraint":"Laboratory screening cannot easily cover huge chemical libraries.","aiRole":"Models predicted activity and highlighted chemical substructures.","documentedResult":"Candidate compounds showed antibacterial activity, including tests in mouse models.","whyItMayMatter":"The results offer starting points for drug development.","unresolvedQuestions":["Optimize candidates and establish safety."]},"evidenceAssessment":{"state":"Experimental","claimConfidence":"unassessed","reviewState":"source-checked","reviewMethod":null,"reviewNote":"Legacy source check; no named human reviewer is recorded in this projection.","lastSourceReview":"2026-09-05","independentVerification":"not-established-by-this-source-review"},"sources":[{"id":"source:mrsa","title":"Discovery of a structural class of antibiotics with explainable deep learning","url":"https://www.nature.com/articles/s41586-023-06887-8","type":"paper"}],"revisions":[],"corrections":[]}