Evidence map›Paper›PMID 32084340›Full record

ArticleCell2020

A Deep Learning Approach to Antibiotic Discovery.

Jonathan M Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina M Donghia, Craig R MacNair, Shawn French, Lindsey A Carfrae, Zohar Bloom-Ackermann and 10 more

Erratum issuedOpen access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 791 papers.

0numbers the graph read from it
0cells of the map it votes in
791citing papers in PubMed
159.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

791 citing papers in PubMed, 2,067 citations in OpenAlex.

  1. Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027
    Review
  2. Article
  3. Article
  4. Review
  5. Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
    Review
  6. Artificial Intelligence-Guided Phenotypic Drug Repurposing Against Streptococcus pneumoniae.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
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  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

731 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 4 institutions in 2 countries.

Jonathan M StokesDepartment of Biological Engineering, Synthetic Biology Center, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Machine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Kevin YangMachine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Kyle SwansonMachine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Wengong JinMachine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Andres Cubillos-RuizDepartment of Biological Engineering, Synthetic Biology Center, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA.
Nina M DonghiaDepartment of Biological Engineering, Synthetic Biology Center, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA.
Craig R MacNairDepartment of Biochemistry and Biomedical Sciences, Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8N 3Z5, Canada.
Shawn FrenchDepartment of Biochemistry and Biomedical Sciences, Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8N 3Z5, Canada.
Lindsey A CarfraeDepartment of Biochemistry and Biomedical Sciences, Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8N 3Z5, Canada.
Zohar Bloom-AckermannBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
Victoria M TranBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Anush Chiappino-PepeWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
Ahmed H BadranBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Ian W AndrewsDepartment of Biological Engineering, Synthetic Biology Center, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA.
Emma J ChoryDepartment of Biological Engineering, Synthetic Biology Center, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
George M ChurchWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA 02139, USA.
Eric D BrownDepartment of Biochemistry and Biomedical Sciences, Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8N 3Z5, Canada.
Tommi S JaakkolaMachine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Regina BarzilayMachine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Abdul Latif Jameel Clinic for Machine Learning in Health, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: regina@csail.mit.edu.
James J CollinsDepartment of Biological Engineering, Synthetic Biology Center, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA; Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA 02139, USA; Abdul Latif Jameel Clinic for Machine Learning in Health, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: jimjc@mit.edu.
Massachusetts Institute of Technology · USBroad Institute · USMcMaster University · CAHarvard University · US

Funding

Functional Interrogation Of Ribosomal Biology Using Continuous EvolutionDP5OD024590 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI BADRAN, AHMED HUSSEIN · 2017 to 2021
$2.2M
CIHR FRN 143215NIH HHS DP5 OD024590
6 · The paper itself

Abstract

Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed predictions on multiple chemical libraries and discovered a molecule from the Drug Repurposing Hub-halicin-that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens including Mycobacterium tuberculosis and carbapenem-resistant Enterobacteriaceae. Halicin also effectively treated Clostridioides difficile and pan-resistant Acinetobacter baumannii infections in murine models. Additionally, from a discrete set of 23 empirically tested predictions from >107 million molecules curated from the ZINC15 database, our model identified eight antibacterial compounds that are structurally distant from known antibiotics. This work highlights the utility of deep learning approaches to expand our antibiotic arsenal through the discovery of structurally distinct antibacterial molecules.

Indexed as

Machine LearningAcinetobacter baumanniiAnimalsAnti-Bacterial AgentsCheminformaticsClostridioides difficileDatabases, ChemicalDrug DiscoveryMiceMice, Inbred BALB CMice, Inbred C57BLMycobacterium tuberculosisSmall Molecule LibrariesThiadiazolesAnti-Bacterial AgentsSmall Molecule LibrariesSU 3327Thiadiazolesantibiotic resistanceantibioticsantibiotic tolerancedrug discoverymachine learning

Identifiers

PMID32084340
PMCPMC8349178
OpenAlexW3007309629

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.