Evidence map›Paper›PMID 42567706›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

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

Xinyu Li, Haojie Fu, Zhe Wang, Xuanzhou Chen, Ruhong Zhang, Xudong Wang, Louis D Zhang, Xiang Li, Datao Li

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xinyu LiDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0009-0004-8886-5419
Haojie FuDepartment of Oral and Craniomaxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhe WangInstitute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China.
Xuanzhou ChenSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
Ruhong ZhangDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0009-0003-1020-9510
Xudong WangDepartment of Oral and Craniomaxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Louis D ZhangThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA.ORCID https://orcid.org/0000-0001-7002-7661
Xiang LiSchool of Pharmacy, Second Military Medical University, Shanghai, China.ORCID https://orcid.org/0000-0002-1098-7713
Datao LiDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

Characteristic Disease Biobank Project of the Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine YBK202511Hainan Provincial Natural Science Foundation of China 326MS0427
6 · The paper itself

Abstract

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.

Indexed as

AI‐designed peptidecGAS‐STING pathwaydiabetic wound healingdual‐responsive hydrogelimmunomodulation

Identifiers

PMID42567706
PMCPMC13451144

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.