ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
HydrogelFinder: A Foundation Model for Efficient Self-Assembling Peptide Discovery Guided by Non-Peptidal Small Molecules.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed.
- Artificial intelligence-assisted design of self-assembling peptide hydrogels for neural regeneration: Principles and opportunities.Bioactive materials · 2027Review
- Immunofunctions of Protein and Carbohydrate Assemblies Modulated by Structures Acrossing Scales as Biomaterials.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- iBitter-HF: A Method for Bitter Peptide Sequence Identification Based on Hybrid Feature Embedding.Foods (Basel, Switzerland) · 2026Article
- Research Progress on Intelligent Prediction, Debittering Technologies, and Multi-Dimensional Evaluation for Bitter Peptides.Foods (Basel, Switzerland) · 2026Review
- Smart responsive hydrogels combined with AI design for tumor therapy.Acta pharmaceutica Sinica. B · 2026Review
- Predicting enhancer-promoter interactions using a stacking-based ensemble strategy.Bioinformatics (Oxford, England) · 2026Article
- Ligand-Induced Electronic Response Enables Predictive QM/MM Simulations.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- BiGvCL: bipartite graph-based cross-domain contrastive learning model for the predicting drug-gene interactions.Briefings in bioinformatics · 2026Article
- TPpred-CMvL: prediction of multi-functional therapeutic peptide using contrast multi-view learning.BMC biology · 2025Article
- ProjFusNet: deep neural network for peptide precursor prediction using projection-fused protein language model and structural features.Journal of cheminformatics · 2025Article
- Accurate prediction of toxicity peptide and its function using multi-view tensor learning and latent semantic learning framework.Bioinformatics (Oxford, England) · 2025Article
- Biomolecular Condensates as Emerging Biomaterials: Functional Mechanisms and Advances in Computational and Experimental Approaches.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides.BMC biology · 2025Article
- EPIPDLF: a pretrained deep learning framework for predicting enhancer-promoter interactions.Bioinformatics (Oxford, England) · 2025Article
- DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions.BMC biology · 2025Article
- Predicting circRNA-disease associations with shared units and multi-channel attention mechanisms.Bioinformatics (Oxford, England) · 2025Article
- AI-driven 3D bioprinting for regenerative medicine: From bench to bedside.Bioactive materials · 2025Review
- Predicting the Mechanical Properties of Supramolecular Gels.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- TargetCLP: clathrin proteins prediction combining transformed and evolutionary scale modeling-based multi-view features via weighted feature integration approach.Briefings in bioinformatics · 2024Article
- Research on Bitter Peptides in the Field of Bioinformatics: A Comprehensive Review.International journal of molecular sciences · 2024Review
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Self-assembling peptides have numerous applications in medicine, food chemistry, and nanotechnology. However, their discovery has traditionally been serendipitous rather than driven by rational design. Here, HydrogelFinder, a foundation model is developed for the rational design of self-assembling peptides from scratch. This model explores the self-assembly properties by molecular structure, leveraging 1,377 self-assembling non-peptidal small molecules to navigate chemical space and improve structural diversity. Utilizing HydrogelFinder, 111 peptide candidates are generated and synthesized 17 peptides, subsequently experimentally validating the self-assembly and biophysical characteristics of nine peptides ranging from 1-10 amino acids-all achieved within a 19-day workflow. Notably, the two de novo-designed self-assembling peptides demonstrated low cytotoxicity and biocompatibility, as confirmed by live/dead assays. This work highlights the capacity of HydrogelFinder to diversify the design of self-assembling peptides through non-peptidal small molecules, offering a powerful toolkit and paradigm for future peptide discovery endeavors.
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Registered trials
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.