ArticleNature biotechnology2026
Target sequence-conditioned design of peptide binders using masked language modeling.
Article in Nature biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Artificial intelligence-assisted design of self-assembling peptide hydrogels for neural regeneration: Principles and opportunities.Bioactive materials · 2027Review
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- Anticancer Peptides: Design Principles, Translational Bottlenecks, and Emerging Opportunities.Molecules (Basel, Switzerland) · 2026Review
- Peptide Aptamers: Innovative Design and Applications in Pathogen Detection.Chembiochem : a European journal of chemical biology · 2026Review
- Immunofunctions of Protein and Carbohydrate Assemblies Modulated by Structures Acrossing Scales as Biomaterials.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Programmable protein degraders enable selective knockdown of pathogenic β-catenin subpopulations in vitro and in vivo.Science advances · 2026Article
- De Novo-Designed Bifunctional Proteins for Targeted Protein Degradation.Journal of the American Chemical Society · 2026Article
- HFGuidedDesign:Chemical science · 2026Article
- Computationally Evidence-Grounded Sequence-First Design of Peptide Binders.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Property guidance for protein sequence generative models with ProteinGuide.Nature biotechnology · 2026Article
- PeptiVerse: A unified platform for therapeutic peptide property prediction.Nature communications · 2026Article
- Recent Progress in Artificial Intelligence in Biosensor Development: From Bioprobe Design to Fabrication and Signal Analysis.Biosensors · 2026Review
- Artificial intelligence in biologic drug discovery: A review of methodological evolution and therapeutic applications.Acta pharmaceutica Sinica. B · 2026Review
- Quorum sensing in streptococci and its peptide-mediated modulation.Bioscience reports · 2026Review
- amyloid-predict and LLPS-predict: Predicting phase separation propensities in the intrinsically disordered proteome.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- EPIC: multi-objective guided diffusion for epitope design in TCR-pMHC complexes.Bioinformatics (Oxford, England) · 2026Article
- Article
- Foundation models in healthcare: a comprehensive review from technical advances to clinical translation.Journal of translational medicine · 2026Review
- Engineered small extracellular vesicles as bioactive materials: Integrating engineering strategies for cargo loading and targeted delivery systems.Bioactive materials · 2026Review
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26 authors.
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Abstract
The computational design of protein-based binders presents unique opportunities to access 'undruggable' targets, but effective binder design often relies on stable three-dimensional structures or structure-influenced latent spaces. Here we introduce PepMLM, a target sequence-conditioned designer of de novo linear peptide binders. Using a masking strategy that positions cognate peptide sequences at the C terminus of target protein sequences, PepMLM finetunes the ESM-2 protein language model to fully reconstruct the binder region, achieving low perplexities matching or improving upon validated peptide-protein sequence pairs. After successful in silico benchmarking with AlphaFold-based docking, we experimentally validate the efficacy of PepMLM through both binding and degradation assays. PepMLM-derived peptides demonstrate sequence-specific binding to cancer and reproductive targets, including NCAM1 and AMHR2, and enable targeted degradation of proteins across diverse disease contexts, from Huntington's disease to live viral infections. Altogether, PepMLM enables the design of candidate binders to any target protein, without requiring structural input, facilitating broad applications in therapeutic development.
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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.