{
  "abstract": "As the burden of antimicrobial resistance continues to rise worldwide, the need for novel antimicrobial therapeutics has become increasingly urgent. Machine learning (ML) has emerged as a promising strategy for accelerating antimicrobial peptide discovery; however, experimental characterization remains essential to define the biological properties and broader applicability of ML-optimized peptides. CIT8 is a 13-residue, citropin-based peptide previously developed through ML-optimization with potent antimicrobial activity against methicillin-resistant Staphylococcus aureus (MRSA). Here, we demonstrate that its activity extends to multidrug-resistant Gram-negative pathogens. Among these, CIT8 displayed the most potent activity against Acinetobacter baumannii , maintaining an MIC of 4 μg/mL against 15 of 16 A. baumannii strains tested, including multiple carbapenem-resistant (CRAB) clinical isolates. At 20 μg/mL (5 × MIC), CIT8 reduced an initial population of approximately 5 × 10 ⁷ CFU/mL of exponential-phase A. baumannii to below the limit of detection within 15 min. Consistent with its rapid bactericidal activity, CIT8 induced rapid, dose-dependent membrane depolarization and permeabilization, accompanied by leakage of intracellular ATP. In addition, CIT8 and, even more notably, its D-enantiomer CIT8-D exhibited strong antibiofilm activity while maintaining relatively low mammalian cytotoxicity, with therapeutic indices of >32 for CIT8 in both cell lines and 16.2 and 18.5 for CIT8-D in HaCaT and HKC-8 cells, respectively. Moreover, CIT8 potentiated the bactericidal activity of meropenem against CRAB, with the combination exhibiting bactericidal synergy by time-kill assay. These findings highlight CIT8 as a promising scaffold for further optimization and preclinical evaluation against multidrug-resistant A. baumannii .",
  "abstract_shown": true,
  "affiliations": [
    "Department of Medicine, Houston Methodist Hospital",
    "Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens",
    "Department of Medicine, Weill Cornell Medical College",
    "School of Pharmaceutical Sciences, Rajiv Gandhi Technological University",
    "School of Biomolecular Engineering and Biotechnology, Rajiv Gandhi Technological University",
    "Department of Electrical and Computer Engineering, National Technical University of Athens"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
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        0,
        1
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      "name": "Charilaos Dellis"
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        2
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      "name": "Biswajit Mishra"
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    {
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        0
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      "name": "Liyang Zhang"
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    {
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        3,
        4
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      "name": "Anindya Basu"
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    {
      "affs": [
        0
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      "name": "Lewis Oscar Felix"
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    {
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        5
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      "name": "Fadi Shehadeh"
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    {
      "affs": [
        0
      ],
      "name": "Narchonai Ganesan"
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    {
      "affs": [
        1
      ],
      "name": "Antonios Kolocouris"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Eleftherios Mylonakis"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9kw50968c8v0j.bib",
  "cited_by": 0,
  "doi": "10.3389/fmicb.2026.1967486",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13724386/?tool=EBI",
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  "landing_url": "https://www.frontiersin.org/articles/10.3389/fmicb.2026.1967486/full",
  "language": "eng",
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  "native_subjects": [
    [
      "heading",
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      "openalex",
      "2404|Antimicrobial Peptides and Activities"
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  "pdf_url": "https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2026.1967486/pdf",
  "pmcid": "PMC13724386",
  "pmid": "42973571",
  "published": "2026-10-19",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/9kw50968c8v0j.ris",
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      "first_seen": "2026-10-30T12:19:12Z",
      "native_id": "10.3389/fmicb.2026.1967486",
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      "url": "https://www.frontiersin.org/articles/10.3389/fmicb.2026.1967486/full"
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2404|Antimicrobial Peptides and Activities",
      "subfield": "microbiology"
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  "title": "CIT8, a machine learning-optimized antimicrobial peptide, exhibits potent activity against carbapenem-resistant Acinetobacter baumannii",
  "title_text": "CIT8, a machine learning-optimized antimicrobial peptide, exhibits potent activity against carbapenem-resistant Acinetobacter baumannii",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T12:20:53Z",
  "url": "https://research.draconitic.com/paper/9kw50968c8v0j",
  "venue": "Frontiers in Microbiology",
  "versions": []
}