What is recorded here?
Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.
Read the original work
- Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
- Publisher-deposited byline: Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
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. Stokes
Full byline of the specified publication; original laboratory roles remain in the source.
Abaucin discovery pipeline · McMaster-led research collaboration · Neural network reported in the paper
Compound prioritization; human-led laboratory confirmation. Source-reported attribution; provider attestation is unavailable.
Research locations and affiliations
Documented mapping · Included in country comparison
Documented countries / regions: Canada, United States
Department of Biochemistry and Biomedical Sciences, Michael G. 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.
English catalogue narrative
Abaucin: a targeted antibacterial lead found with AI
Used a neural network to prioritize compounds against Acinetobacter baumannii, followed by experiments identifying abaucin and activity in a mouse wound model.
Scientific scope
The result is a preclinical lead with a narrow antibacterial spectrum. Clinical efficacy, approval and a complete drug-development outcome are outside this paper.
Reading status
This 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.
People and systems
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. Stokes
Full byline of the specified publication; original laboratory roles remain in the source.
Abaucin discovery pipeline / McMaster-led research collaboration / Neural network reported in the paper: Compound prioritization; human-led laboratory confirmation (source reported).