Deep learning speeds the search for new antibiotic scaffolds

Yumeng Zhang; Jiangning Song; Cesar de la Fuente-Nunez

doi:10.1038/s41587-025-02806-6

Deep learning speeds the search for new antibiotic scaffolds

Yumeng Zhang, Jiangning Song (Leading Author), Cesar de la Fuente-Nunez (Leading Author)

Research output: Contribution to journal › Comment / Debate › Other › peer-review

Abstract

A deep learning model trained on experimental data from high-throughput screening identifies structurally novel antimicrobial compounds.

Original language	English
Number of pages	3
Journal	Nature Biotechnology
DOIs	https://doi.org/10.1038/s41587-025-02806-6
Publication status	Accepted/In press - 2025

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title = "Deep learning speeds the search for new antibiotic scaffolds",

abstract = "A deep learning model trained on experimental data from high-throughput screening identifies structurally novel antimicrobial compounds.",

author = "Yumeng Zhang and Jiangning Song and \{de la Fuente-Nunez\}, Cesar",

note = "Publisher Copyright: {\textcopyright} Springer Nature America, Inc. 2025.",

year = "2025",

doi = "10.1038/s41587-025-02806-6",

language = "English",

journal = "Nature Biotechnology",

issn = "1087-0156",

publisher = "Nature Publishing Group",

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TY - JOUR

T1 - Deep learning speeds the search for new antibiotic scaffolds

AU - Zhang, Yumeng

A2 - Song, Jiangning

A2 - de la Fuente-Nunez, Cesar

PY - 2025

Y1 - 2025

N2 - A deep learning model trained on experimental data from high-throughput screening identifies structurally novel antimicrobial compounds.

AB - A deep learning model trained on experimental data from high-throughput screening identifies structurally novel antimicrobial compounds.

UR - https://www.scopus.com/pages/publications/105019766128

U2 - 10.1038/s41587-025-02806-6

DO - 10.1038/s41587-025-02806-6

M3 - Comment / Debate

AN - SCOPUS:105019766128

SN - 1087-0156

JO - Nature Biotechnology

JF - Nature Biotechnology

ER -

Deep learning speeds the search for new antibiotic scaffolds

Abstract

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