ArticleCommunications biology2023
SaLT&PepPr is an interface-predicting language model for designing peptide-guided protein degraders.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 42 citations in OpenAlex.
- 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
- Deep learning-driven discovery and mechanism of action study of a minimalist conopeptide targetingActa pharmaceutica Sinica. B · 2026Article
- Deep learning-driven decoding of ubiquitination: from regulatory mechanisms to targeted protein degradation.Biology direct · 2026Review
- Target sequence-conditioned design of peptide binders using masked language modeling.Nature biotechnology · 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
- Antioxidant and Antiproliferative Activities of Hemp Seed Proteins (International journal of molecular sciences · 2025Article
- Towards directed therapy for fusion-positive rhabdomyosarcoma.Pharmacology & therapeutics · 2025Review
- Accurate de novo design of high-affinity protein-binding macrocycles using deep learning.Nature chemical biology · 2025Article
- Pharmacological considerations for next-generation protein therapeutics in cardiovascular disease.The Journal of pharmacology and experimental therapeutics · 2025Review
- Leveraging learned representations and multitask learning for lysine methylation site discovery.bioRxiv : the preprint server for biology · 2025Article
- PTM-Mamba: a PTM-aware protein language model with bidirectional gated Mamba blocks.Nature methods · 2025Article
- Programmable protein stabilization with language model-derived peptide guides.Nature communications · 2025Article
- Protein-Based Degraders: From Chemical Biology Tools to Neo-Therapeutics.Chemical reviews · 2025Review
- FusOn-pLM: a fusion oncoprotein-specific language model via adjusted rate masking.Nature communications · 2025Article
- De novo design of peptide binders to conformationally diverse targets with contrastive language modeling.Science advances · 2025Article
- Leveraging large language models for peptide antibiotic design.Cell reports. Physical science · 2025Article
- AccuratebioRxiv : the preprint server for biology · 2024Article
- PepCA: Unveiling protein-peptide interaction sites with a multi-input neural network model.iScience · 2024Article
Corrections and comments
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Authors and funding
21 authors at 2 institutions in 1 country.
Funding
Abstract
Protein-protein interactions (PPIs) are critical for biological processes and predicting the sites of these interactions is useful for both computational and experimental applications. We present a Structure-agnostic Language Transformer and Peptide Prioritization (SaLT&PepPr) pipeline to predict interaction interfaces from a protein sequence alone for the subsequent generation of peptidic binding motifs. Our model fine-tunes the ESM-2 protein language model (pLM) with a per-position prediction task to identify PPI sites using data from the PDB, and prioritizes motifs which are most likely to be involved within inter-chain binding. By only using amino acid sequence as input, our model is competitive with structural homology-based methods, but exhibits reduced performance compared with deep learning models that input both structural and sequence features. Inspired by our previous results using co-crystals to engineer target-binding "guide" peptides, we curate PPI databases to identify partners for subsequent peptide derivation. Fusing guide peptides to an E3 ubiquitin ligase domain, we demonstrate degradation of endogenous β-catenin, 4E-BP2, and TRIM8, and highlight the nanomolar binding affinity, low off-targeting propensity, and function-altering capability of our best-performing degraders in cancer cells. In total, our study suggests that prioritizing binders from natural interactions via pLMs can enable programmable protein targeting and modulation.
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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.