{ "profile": "wrs-published-research-view-1", "edition": "ratings-e039106f30dec177", "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS", "entry": { "id": "abaucin-discovery", "title": "Abaucin: a targeted antibacterial lead found with AI", "summary": "Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.", "boundary": "The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.", "area": "Antibiotic discovery", "topic": "Life & medicine", "year": 2023, "lane": "AI", "result": "EMPIRICAL", "package_id": "abaucin-discovery", "target": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "humans": [ "Gary Liu", "Denise B. Catacutan", "Khushi Rathod", "Kyle Swanson", "Wengong Jin", "Jody C. Mohammed", "Anush Chiappino-Pepe", "Saad A. Syed", "Meghan Fragis", "Kenneth Rachwalski", "Jakob Magolan", "Michael G. Surette", "Brian K. Coombes", "Tommi S. Jaakkola", "Regina Barzilay", "James J. Collins", "Jonathan M. 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DeGroote Institute for Infectious Disease Research, David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, Canada.; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.; Department of Genetics, Harvard Medical School, Boston, MA, USA.; Department of Medicine, Department of Biochemistry and Biomedical Sciences, Farncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Ontario, Canada.; Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario, Canada.; Abdul Latif Jameel Clinic for Machine Learning in Health, Massachusetts Institute of Technology, Cambridge, MA, USA.; Department of Biological Engineering, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA.", "source_url": "https://europepmc.org/article/MED/37231267", "target": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "basis": "RESEARCH_LOCATION_OR_PAPER_AFFILIATION", "reviewed_on": "2026-09-12", "nationality_inferred": false, "coverage_status": "COMPLETE", "country_labels": { "CA": "Canada", "US": "United States" } }, "points": "6000", "published_grade": { "id": "abaucin-discovery", "entry_id": "abaucin-discovery", "band": "B", "modifier": null, "target": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "what_changed": "Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.", "scope": "Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model. Scope limitation: The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.", "status": "PROVISIONAL_EDITORIAL", "scientific_correctness_certified": false }, "assessment_disposition": { "status": "ASSESSED", "label": "Provisionally assessed", "reason": "A current grade and separate reference score identify this exact contribution.", "target": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "edition": "ratings-e039106f30dec177" } }, "version": { "kind": "PUBLIC_RECORD_VIEW", "previous": null, "published_at": "2026-09-12T00:00:00Z", "publisher": { "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33", "role": "WRS_EDITORIAL_PUBLICATION" }, "record": { "contributors": [], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii", "url": "https://www.nature.com/articles/s41589-023-01349-8" } }, { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-1", "kind": "source_reference", "source": { "citation": "Publisher-deposited byline: Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii", "url": "https://api.crossref.org/works/10.1038%2Fs41589-023-01349-8" } } ], "origin": "AGENT_NATIVE", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.", "domain": "Antibiotic discovery" }, "sources": [ { "citation": "Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii", "url": "https://www.nature.com/articles/s41589-023-01349-8" }, { "citation": "Publisher-deposited byline: Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii", "url": "https://api.crossref.org/works/10.1038%2Fs41589-023-01349-8" } ], "statement": "# Abaucin: a targeted antibacterial lead found with AI\n\nUsed a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.\n\n## Scientific scope\n\nThe result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nGary Liu; Denise B. Catacutan; Khushi Rathod; Kyle Swanson; Wengong Jin; Jody C. Mohammed; Anush Chiappino-Pepe; Saad A. Syed; Meghan Fragis; Kenneth Rachwalski; Jakob Magolan; Michael G. Surette; Brian K. Coombes; Tommi S. Jaakkola; Regina Barzilay; James J. Collins; Jonathan M. Stokes\n\nFull byline of the specified publication; original laboratory roles remain in the source.\n\nAbaucin discovery pipeline / McMaster-led research collaboration / Neural network reported in the paper: Compound prioritization; human-led laboratory confirmation (source reported).\n\n## Original sources\n\n- [Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii](https://www.nature.com/articles/s41589-023-01349-8)\n- [Publisher-deposited byline: Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii](https://api.crossref.org/works/10.1038%2Fs41589-023-01349-8)\n", "summary": "Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.", "title": "Abaucin: a targeted antibacterial lead found with AI" }, "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "source_ref": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:a771de7fb90d05bbafdcefd202de1d9c792acbe36a379ac3b1c6bbd1261ce7dd" }, "target": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "abaucin-discovery", "entry_id": "abaucin-discovery", "revision": 1, "title": "Abaucin: a targeted antibacterial lead found with AI", "context": "Antibiotic discovery", "track": "Scoped scientific or research-capability contribution", "band": "B", "modifier": null, "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-09-14", "evidence_cutoff": "2026-09-14", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.", "scope": "Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model. Scope limitation: The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.", "evidence_summary": "Assessment uses the catalogue-linked source evidence for the stated contribution. The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.", "references": [ { "title": "Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii", "url": "https://www.nature.com/articles/s41589-023-01349-8", "locator": "Retained catalogue source evidence; Published abstract or selected source passages and bibliographic identity read; not a full proof or experimental replication." }, { "title": "Publisher-deposited byline: Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii", "url": "https://api.crossref.org/works/10.1038%2Fs41589-023-01349-8", "locator": "Retained catalogue source evidence; Complete deposited byline retained locally with a checksum; bibliographic evidence only." } ], "roles": [ { "who": "The research collaboration listed in the linked record and source byline", "credit": "SCIENCE", "did": "Collective scoped contribution. The complete recorded byline remains in the research record; this label does not collapse people into one individual." }, { "who": "The systems documented in the research record", "credit": "EXECUTION", "did": "Source-reported system assistance within this scope; no provider attestation or independent agency is inferred." } ], "target": { "record_id": "urn:uuid:1d437cd8-ee8d-440d-af2b-97752e74cd5f", "version": 1, "content_hash": "sha256:f8fce283e9847da505a4659a3ee35684bba5d5a7a97f6dd85eff011f98612058" }, "scientific_correctness_certified": false, "independent_expert_calibration": false, "method": "PROPRIETARY", "points": "6000" }, "canonical_agent_submission": false, "scientific_verification_awarded": false, "reader_guide": null, "reading_status": "SOURCE_LINKED_NOTE" }