Throw out an oligopeptide to catch a protein: Deep learning and natural language processing-screened tripeptide PSP promotes Osteolectin-mediated vascularized bone regeneration

Yu Chen; Long Chen; Jinyang Wu; Xiaofeng Xu; Chengshuai Yang; Yong Zhang; Xinrong Chen; Kaili Lin; Shilei Zhang

Bioactive Materials (Apr 2025)

Throw out an oligopeptide to catch a protein: Deep learning and natural language processing-screened tripeptide PSP promotes Osteolectin-mediated vascularized bone regeneration

Yu Chen,
Long Chen,
Jinyang Wu,
Xiaofeng Xu,
Chengshuai Yang,
Yong Zhang,
Xinrong Chen,
Kaili Lin,
Shilei Zhang

Affiliations

Yu Chen: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China
Long Chen: Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China
Jinyang Wu: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China
Xiaofeng Xu: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China
Chengshuai Yang: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China
Yong Zhang: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China; Corresponding author.
Xinrong Chen: Academy for Engineering and Technology, Fudan University, Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Shanghai, 200000, China; Corresponding author.
Kaili Lin: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China; Corresponding author.
Shilei Zhang: Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stom, Shanghai, 200011, China; Corresponding author.

Journal volume & issue: Vol. 46
pp. 37 – 54

Abstract

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Angiogenesis is imperative for bone regeneration, yet the conventional cytokine therapies have been constrained by prohibitive costs and safety apprehensions. It is urgent to develop a safer and more efficient therapeutic alternative. Herein, utilizing the methodologies of Deep Learning (DL) and Natural Language Processing (NLP), we proposed a paradigm algorithm that amalgamates Word2vec with a TF-IDF variant, TF-IIDF, to deftly discern potential pro-angiogenic peptides from intrinsically disordered regions (IDRs) of 262 related proteins, where are fertile grounds for developing safer and highly promising bioactive peptides. After the evaluation of the candidate oligopeptides, one tripeptide, PSP, emerged as particularly notable for its exceptional ability to stimulate the vascularization of endothelial cells (ECs), enhance vascular-osteo communication, and then boost the osteogenic differentiation of bone marrow stem cells (BMSCs), evidenced in mouse critical-sized cranial model. Moreover, we found that PSP serves as a ‘priming’ agent, activating the body's innate ability to produce Osteolectin (Oln) — prompting ECs to release small extracellular vesicles (sEVs) enriched with Oln to facilitate bone formation. In summary, our study established a precise and efficient composite model of DL and NLP to screen bioactive peptides, opening an avenue for the development of various peptide-based therapeutic strategies applicable to a broader range of diseases.

Published in Bioactive Materials

ISSN: 2452-199X (Online)
Publisher: KeAi Communications Co., Ltd.
Country of publisher: China
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials; Science: Biology (General)
Website: https://www.keaipublishing.com/en/journals/bioactive-materials/

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