Machine Learning-Identified Potent Antimicrobial Peptides Against Multidrug-Resistant Bacteria and Skin Infections

Antibiotics, vol. 14, pp. 1172

Abstract

Background: The escalating global crisis of antibiotic resistance necessitates the discovery of novel antimicrobial agents. Antimicrobial peptides (AMPs) represent a promising alternative to combat multidrug-resistant (MDR) pathogens. Because traditional AMP discovery is labour-intensive and costly, machine learning (ML) is applied to identify AMPs effective against MDR bacteria and skin infections. Methods: The ML-based CalcAMP model predicts the antimicrobial activity of 16,384 unique 14-amino-acid peptide sequences, resulting in a novel Guided Designed Smart antimicrobial Therapeutic (GDST) peptide catalogue. Parent sequences and retro-inverso (RI) variants of two prime GDST peptides undergo extensive testing against MDR bacteria and in skin infection models. Results: GDST-038 and GDST-045, along with their RI variants, show potent antimicrobial activity against Acinetobacter baumannii and Staphylococcus aureus, rapidly depolarizing the cytoplasmic membrane, exhibiting broad-spectrum bactericidal effects against ESKAPE pathogens, and causing minimal haemolysis. RI variants display superior A. baumannii biofilm killing compared to parent sequences, while all GDST peptides achieve >3-log reductions in S. aureus biofilm CFU within 24 h. Potent efficacy is observed in a 3D human skin epidermal infection model, with elimination of S. aureus at ≥15 μM. No resistance develops after 22 passages. Conclusions: ML-driven screening enables rapid identification of two novel candidate AMPs, highlighting the therapeutic potential of GDST peptides for MDR bacterial infections.

Authors 10

1. Gizem Babuççu

   Amsterdam University Medical Centers · University of Amsterdam

   Affiliation as printed

   Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Centre, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands

2. Nikitha Vavilthota

   Amsterdam University Medical Centers · University of Amsterdam

   Affiliation as printed

   Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Centre, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands

3. Colin Bournez Aachen Computational Drug Discovery Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Computational Drug Discovery, Medicinal Chemistry, Leiden Academic Center for Drug Research, Leiden University, 2300 RA Leiden, The Netherlands

4. Leonie de Boer

   Amsterdam University Medical Centers · University of Amsterdam

   Affiliation as printed

   Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Centre, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands

5. Robert A. Cordfunke Aachen Department of Immunology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Immunology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands

6. Peter H. Nibbering Aachen Department of Infectious Diseases

   Leiden University Medical Center

   Affiliation as printed

   Department of Infectious Diseases, Leiden University Medical Center, 2300 RC Leiden, The Netherlands

7. Gerard J. P. van Westen Aachen Computational Drug Discovery Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Computational Drug Discovery, Medicinal Chemistry, Leiden Academic Center for Drug Research, Leiden University, 2300 RA Leiden, The Netherlands

8. Jan Wouter Drijfhout Aachen Department of Immunology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Immunology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands

9. Sebastian A. J. Zaat corresponding

   Amsterdam University Medical Centers · University of Amsterdam

   Affiliation as printed

   Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Centre, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands

10. Martijn Riool corresponding

    University Hospital Regensburg · Amsterdam University Medical Centers · University of Regensburg · University of Amsterdam

    Affiliation as printed

    Department of Medical Microbiology and Infection Prevention, Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Centre, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands

    Laboratory for Experimental Trauma Surgery, Department of Trauma Surgery, University Hospital Regensburg, 93053 Regensburg, Germany