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Transl. Med."],"published-print":{"date-parts":[[2026,6,17]]},"abstract":"<jats:p>\n                    <jats:italic toggle=\"yes\">Neisseria gonorrhoeae<\/jats:italic>\n                    is a common Gram-negative pathogen with increasing resistance to all recommended antibiotics. There is a critical need to improve the efficiency of the antibiotic hit discovery process to replenish the drug development pipeline. Here, we show that deep learning models can augment high-throughput screens to identify readily available molecules with narrow-spectrum activity against difficult-to-treat strains of\n                    <jats:italic toggle=\"yes\">N. gonorrhoeae<\/jats:italic>\n                    . We phenotypically tested 38,650 small molecules for\n                    <jats:italic toggle=\"yes\">N. gonorrhoeae<\/jats:italic>\n                    growth inhibition to train a predictive graph neural network (GNN) model. We benchmarked the model\u2019s performance against other architectures, including a large language model, and found that GNNs more accurately identify active, drug-like molecules that are structurally distinct from the training set and known antibiotics. Using the model to virtually screen ~6 million compounds, we identified 213 compounds for experimental validation and found that 83 (39%) inhibited\n                    <jats:italic toggle=\"yes\">N. gonorrhoeae<\/jats:italic>\n                    growth. Two of these compounds were structurally dissimilar to existing antibiotics, maintained potency against multidrug-resistant\n                    <jats:italic toggle=\"yes\">N. gonorrhoeae<\/jats:italic>\n                    strains in vitro, exhibited promising selectivity indices, and were rapidly bactericidal with low frequencies of resistance. Proteomic studies revealed their distinct mechanisms of action, with one compound targeting alanine racemase, an enzyme involved in the essential process of peptidoglycan synthesis. Furthermore, the compounds showed early promise in reducing\n                    <jats:italic toggle=\"yes\">N. gonorrhoeae<\/jats:italic>\n                    titers in a human vagina-on-a-chip infection model and a mouse vaginal infection model. Our work establishes the deep learning\u2013enabled discovery of selective antibacterial compounds against\n                    <jats:italic toggle=\"yes\">N. gonorrhoeae<\/jats:italic>\n                    as a much-needed hit discovery tool to address the growing crisis of antimicrobial resistance for this pathogen.\n                  <\/jats:p>","DOI":"10.1126\/scitranslmed.ads4699","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T17:58:46Z","timestamp":1781719126000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":5,"title":["Deep learning\u2013enabled discovery of antibiotics effective against\n                    <i>Neisseria gonorrhoeae<\/i>"],"prefix":"10.1126","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0309-368X","authenticated-orcid":true,"given":"Melis N.","family":"Anahtar","sequence":"first","affiliation":[{"name":"Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA."},{"name":"Departments of Pathology and Medicine, Massachusetts General Hospital, Boston, MA 02114, USA."},{"name":"Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA."},{"name":"Institute for Medical Engineering and Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3430-5924","authenticated-orcid":true,"given":"Jacqueline A.","family":"Valeri","sequence":"additional","affiliation":[{"name":"Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA."},{"name":"Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA."},{"name":"Institute for Medical Engineering and Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9747-9748","authenticated-orcid":true,"given":"Seyed Majed","family":"Modaresi","sequence":"additional","affiliation":[{"name":"Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA."},{"name":"Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA."},{"name":"Institute for Medical Engineering and Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7936-4442","authenticated-orcid":true,"given":"Aarti","family":"Krishnan","sequence":"additional","affiliation":[{"name":"Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA."},{"name":"Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA."},{"name":"Institute for Medical Engineering and Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."},{"name":"Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0826-904X","authenticated-orcid":true,"given":"Nina M.","family":"Donghia","sequence":"additional","affiliation":[{"name":"Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7849-8078","authenticated-orcid":true,"given":"Samantha G.","family":"Palace","sequence":"additional","affiliation":[{"name":"Department of Immunology and Infectious Diseases, Harvard T. 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Paulson School of Engineering and Applied Sciences, Cambridge, MA 02539, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5560-8246","authenticated-orcid":true,"given":"James J.","family":"Collins","sequence":"additional","affiliation":[{"name":"Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA."},{"name":"Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA."},{"name":"Institute for Medical Engineering and Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","reference":[{"key":"e_1_3_2_2_2","unstructured":"Centers for Disease Control and Prevention \u201cAntibiotic resistant threats in the United States 2019\u201d (US Department of Health and Human Services CDC 2019)."},{"key":"e_1_3_2_3_2","unstructured":"J. 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