ArticleProceedings of the National Academy of Sciences of the United States of America2019
Design of self-assembly dipeptide hydrogels and machine learning via their chemical features.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
- Artificial intelligence-assisted design of self-assembling peptide hydrogels for neural regeneration: Principles and opportunities.Bioactive materials · 2027Review
- AI for bioactive materials: From material design to biological applications.Bioactive materials · 2026Review
- Artificial intelligence and peripheral neuropathies: Strategies for the development, application, and repair of regenerative biomaterials.Neural regeneration research · 2026Article
- Organoid intelligence: a promising paradigm for autism spectrum disorder research.Molecular psychiatry · 2026Review
- Biomass-Derived Hydrogels for Load-Bearing Connective Tissue Repair: Integrative Reinforcement, Bio-Functional Design, and Emerging Pathways Toward Clinical Translation.Advanced healthcare materials · 2026Review
- A Computational Strategy for Identifying Self-Assembling Food-Derived Molecules for Antiparasitic Nanotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Machine-Learning-Enabled Hydrogel Biosensors for Wearable Health Monitoring.Gels (Basel, Switzerland) · 2026Review
- Preparation strategies and biomedical applications of DNA hydrogels.Chemical science · 2026Review
- Research Progress in Artificial Intelligence-Assisted Preparation of High-Quality Biomaterials.ACS omega · 2026Review
- Rethinking Nature's Pharmacy: AI Era and Natural Product Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Targeting delayed healing tissues: immune reprogramming of adaptive immune cells by biomaterials.Regenerative biomaterials · 2026Review
- Inflammasomes meet organoids and artificial intelligence: unraveling the complexity of gynecological inflammation.Frontiers in immunology · 2026Review
- Natural Product Based Hydrogels in Biomedicine: Design Strategies and Crosslinking Mechanisms.International journal of nanomedicine · 2026Review
- Spatiotemporally controlled delivery of biomacromolecules via injectable hydrogels for precision modulation of the tumor immune microenvironment.Journal of nanobiotechnology · 2025Review
- Intelligent Sensing: The Emerging Integration of Machine Learning and Soft Sensors Based on Hydrogels and Ionogels.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Revolutionizing neural regeneration with smart responsive materials: Current insights and future prospects.Bioactive materials · 2025Review
- Article
- Substitution of tyrosine with electron-deficient aromatic amino acids improves Ac-PHF6 self-assembly and hydrogelation.RSC advances · 2025Article
- Applications of flexible materials in health management assisted by machine learning.RSC advances · 2025Review
- Multifunctional Hydrogels for Advanced Cancer Treatment: Diagnostic Imaging and Therapeutic Modalities.Gels (Basel, Switzerland) · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hydrogels that are self-assembled by peptides have attracted great interest for biomedical applications. However, the link between chemical structures of peptides and their corresponding hydrogel properties is still unclear. Here, we showed a combinational approach to generate a structurally diverse hydrogel library with more than 2,000 peptides and evaluated their corresponding properties. We used a quantitative structure-property relationship to calculate their chemical features reflecting the topological and physicochemical properties, and applied machine learning to predict the self-assembly behavior. We observed that the stiffness of hydrogels is correlated with the diameter and cross-linking degree of the nanofiber. Importantly, we demonstrated that the hydrogels support cell proliferation in culture, suggesting the biocompatibility of the hydrogel. The combinatorial hydrogel library and the machine learning approach we developed linked the chemical structures with their self-assembly behavior and can accelerate the design of novel peptide structures for biomedical use.
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