AI Designed Conformation Locking Peptides Target STING to Restore Diabetic Wound Healing

Diabetic foot ulcers are a major complication of diabetes characterized by persistent inflammation and impaired tissue repair, in part driven by aberrant activation of the cGAS-STING innate immune pathway. Precision immunomodulation in the protease-rich wound microenvironment remains challenging because therapeutic efficacy requires both localized retention and responsiveness to pathological cues. Here, we developed an integrated AI-to-biomaterial strategy for diabetic wound repair by coupling generative AI-guided peptide discovery with microenvironment-responsive local delivery. A structure-guided deep-learning pipeline integrating RFDiffusion, ProteinMPNN, and AlphaFold2-multimer identified SCP-1, a conformation-locking peptide designed to stabilize the inactive STING dimer. To enable therapeutic translation, SCP-1 was incorporated into a dual-responsive hydrogel (Gel-SCP-1) that provides in situ gelation and MMP-9-triggered release in the wound bed. Gel-SCP-1 suppressed STING-TBK1-IRF3 signaling, reduced inflammatory and oxidative stress, promoted reparative macrophage polarization, and enhanced angiogenic activity. In a full-thickness excisional wound model in db/db diabetic mice, Gel-SCP-1 significantly accelerated wound closure and improved tissue regeneration, including enhanced re-epithelialization and collagen remodeling. These findings establish an AI-to-biomaterial therapeutic paradigm for precision immunoregenerative therapy in chronic diabetic wounds.