A Self-Adaptive CoNi-Based Metal-Organic Framework for Autonomous Antibacterial Efficacy and Anti-Inflammatory Resolution in Accelerated Wound Healing.

Authors

Yu Chen, Jinyao Zheng, Qianyu Guo, Yuanhao Zhang, Mingfei Zhai, Ying Lin, Miaomiao Zhang, Jilin Tang

Published in

Advanced healthcare materials. Pages e71851. Oct 15, 2026. Epub Oct 15, 2026.

Abstract

Delayed healing of bacterially infected wounds stems from drug-resistant bacterial invasion and excessive reactive oxygen species (ROS)-driven inflammation, which necessitating strategies that simultaneously eradicate pathogens and resolve inflammation. We designed a bimetallic CoNi-based metal-organic framework (CoNi-MOF) with enhanced multienzyme-like activities: oxidase-like (OXD-like), peroxidase-like (POD-like), and catalase-like (CAT-like) activities. The superior performance arises from the synergy between Co and Ni, which shifts the d-band center of Co closer to the Fermi level than those in Co-MOF and Ni-MOF. This electronic structure enhancement facilitates substrate adsorption and lowers reaction energy barriers, accounting for the strong enzyme-like activities of CoNi-MOF. At acidic infection sites, OXD-like and POD-like activities are activated to generate antibacterial ROS, effectively eliminating drug-resistant bacteria. As bacterial clearance occurs and the wound returns to neutrality, CoNi-MOF exhibits CAT-like activity and radical scavenging capabilities to eliminate excess ROS, thereby restoring oxidative balance and mitigating inflammation. Moreover, CoNi-MOF promotes macrophage polarization from the pro-inflammatory M1 phenotype toward the pro-regenerative M2 phenotype. This pH-responsive enzymatic activity offers a self-adaptive therapeutic strategy, as validated by in vivo studies showing accelerated wound healing. This self-adaptive nanozyme platform integrates antibacterial, antioxidant, and immunomodulatory functions, offering a promising antibiotic-free treatment for drug-resistant bacterial wound infections.

PMID:
42876428
Bibliographic data and abstract were imported from PubMed on 15 Oct 2026.

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