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Bioactive sericin scaffolds with allantoin-acetamide eutectic for enhanced wound healing

  • Muhammad Naseer , Nawab Ali , Iram Bibi ORCID logo , Syed Waqar Hussain Shah , Liaqat Rasheed , Wajid Rehman ORCID logo EMAIL logo , Abdullah Y. Alzahrani and Obaid-Ur-Rahman Abid
Published/Copyright: August 6, 2025

Abstract

Smart wound dressings that respond to the wound environment have emerged as innovative therapeutic platforms, aiming to control infection, reduce inflammation, and promote vascularization for effective healing. Herein, an innovative eutectic system combining acetamide and allantoin (AAM) integrated with sericin peptides (SS) for enhanced wound healing applications is reported. The binary AAM system exhibited superior physicochemical properties, utilizing acetamide’s anti-inflammatory effects and allantoin’s regenerative capabilities. The binary AAM system exhibited superior physicochemical properties, with molecular modeling revealing optimal donor-acceptor interactions and FTIR confirming complex intermolecular networks in SS-incorporated scaffolds. The SS-containing scaffolds showed significantly enhanced wound healing efficacy in a mouse model compared to non-functionalized AAM systems, with accelerated wound closure through synergistic interactions. This integration of eutectic systems with bioactive peptides presents a promising platform for advanced wound healing therapeutics, offering improved drug delivery and tissue regeneration.


Corresponding authors: Wajid Rehman, Department of Chemistry, Hazara University Mansehra, Mansehra, 21120, Pakistan, e-mail:

Acknowledgments

The authors extend their appreciation to Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology for valuable Research cooperation.

  1. Research ethics: Agreed and fulfil the research ethics.

  2. Informed consent: No consent required.

  3. Author contributions: MN: Methodology; IB: Conceptualization, Supervision; SWHS: supervision, Conceptualization; NA; methodology; LR: Data Curation; WR: MS Writing, Conceptualization, Validation; AYA: Softaware, data analysis.

  4. Use of Large Language Models, AI and Machine Learning Tools: No tool used.

  5. Conflict of interest: No conflict of interest.

  6. Research funding: No funding.

  7. Data availability: The data could be made available, if requested.

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Received: 2025-05-09
Accepted: 2025-07-27
Published Online: 2025-08-06

© 2025 IUPAC & De Gruyter

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