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Updated: Jun 2, 2026

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Design of Multifunctional Bioactive Peptides for Potential Application in Food Packaging: A

Sree Nithish Reddy Gunapati1, Sathish Kumar Gunaseelan1, Arnab Dutta1

  • 1Chemical Engineering Department Birla, Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Medchal District, Hyderabad 500078, Telangana, India.

ACS Omega
|June 1, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed a computational framework using machine learning to design multifunctional bioactive peptides for active food packaging. This approach efficiently identifies peptides with antioxidant, antifungal, and antibacterial properties, enhancing food safety and reducing foodborne diseases.

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Food Science

Background:

  • Multifunctional bioactive peptides offer significant potential for active packaging systems to combat foodborne diseases.
  • Discovering peptides with antioxidant, antifungal, and antibacterial properties is challenging due to the vast sequence space.

Purpose of the Study:

  • To develop a computational framework integrating machine learning and optimization for designing multifunctional bioactive peptides.
  • To create a tool for efficient screening and design of peptides with desired bioactivities.

Main Methods:

  • Developed three machine-learning-based binary classification models to predict antioxidant, antifungal, and antibacterial activities.
  • Integrated these models into an optimization framework to generate novel peptide sequences.
  • Analyzed amino acid compositions of designed peptides to confirm characteristic properties.

Main Results:

  • Machine learning models achieved high accuracies: 82.37% (antioxidant), 95.49% (antifungal), and 96.75% (antibacterial).
  • The computational framework successfully designed novel peptides exhibiting multifunctional bioactivities.
  • Designed peptides contained significant proportions of amino acids characteristic of antioxidant, antifungal, and antibacterial activities.

Conclusions:

  • The proposed computational framework effectively designs multifunctional bioactive peptides.
  • These peptides show potential for application in active food packaging systems.
  • A user-friendly tool is available to accelerate the design process for these peptides.