ArticleScience advances2025
De novo design of peptide binders to conformationally diverse targets with contrastive language modeling.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed.
- Article
- Article
- Programmable protein degraders enable selective knockdown of pathogenic β-catenin subpopulations in vitro and in vivo.Science advances · 2026Article
- Computationally Evidence-Grounded Sequence-First Design of Peptide Binders.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- AI-GuidedJournal of the American Chemical Society · 2026Article
- Deep learning-driven discovery and mechanism of action study of a minimalist conopeptide targetingActa pharmaceutica Sinica. B · 2026Article
- Artificial intelligence in biologic drug discovery: A review of methodological evolution and therapeutic applications.Acta pharmaceutica Sinica. B · 2026Review
- Target sequence-conditioned design of peptide binders using masked language modeling.Nature biotechnology · 2026Article
- TCRBinder: Unified pre-trained language model with paired-chain synergy for predicting T-cell receptor binding specificity.PLoS computational biology · 2026Article
- Article
- Plant-Produced Viral Nanoparticles Decorated with Nanobodies Against HER2 Improve Retention and Recruitment of Immune Cells in Solid Tumors.Advanced healthcare materials · 2026Article
- From CRISPR functional genomics to synthetic interventions: engineering antiviral strategies.Journal of virology · 2026Review
- DrugBLIP: exploring the protein-molecule interaction mechanisms with a multi-task learning graph transformer.Bioinformatics (Oxford, England) · 2026Article
- Review
- Intrinsic dataset features drive mutational effect prediction by protein language models.bioRxiv : the preprint server for biology · 2026Article
- Generative design and validation of therapeutic peptides for glioblastoma based on a potential target ATP5A.Briefings in bioinformatics · 2026Article
- Peptide-functionalized nanoparticles for brain-targeted therapeutics.Drug delivery and translational research · 2026Review
- Leveraging learned representations and multitask learning for lysine methylation site discovery.Scientific reports · 2026Article
- Peptide-based drug design using generative AI.Chemical communications (Cambridge, England) · 2026Review
Corrections and comments
- Update of
Authors and funding
20 authors.
Funding
Abstract
Designing binders to target undruggable proteins presents a formidable challenge in drug discovery. In this work, we provide an algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein. To do this, we propose a process to generate naturalistic peptide candidates through Gaussian perturbation of the peptidic latent space of the ESM-2 protein language model and subsequently screen these novel sequences for target-selective interaction activity via a contrastive language-image pretraining (CLIP)-based contrastive learning architecture. By integrating these generative and discriminative steps, we create a Peptide Prioritization via CLIP (PepPrCLIP) pipeline and validate highly ranked, target-specific peptides experimentally, both as inhibitory peptides and as fusions to E3 ubiquitin ligase domains. PepPrCLIP-derived constructs demonstrate functionally potent binding and degradation of conformationally diverse, disease-driving targets in vitro. In total, PepPrCLIP empowers the modulation of previously inaccessible proteins without reliance on stable and ordered tertiary structures.
Indexed as
Identifiers
What OpenQuestion holds
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.