ArticleCell systems2024
AlphaFold2 enables accurate deorphanization of ligands to single-pass receptors.
Article in Cell systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Exercise-induced myokines in metabolic regulation: mechanisms, mimetics, and translational potential.Archives of pharmacal research · 2026Review
- Elucidating the Structure and Activation Mechanisms of GPCRs Using Modern Computational and AI Tools.Cell biochemistry and biophysics · 2026Review
- PPIscreenML is a method for structure-based screening of protein-protein interactions using AlphaFold.eLife · 2026Article
- Analysis and engineering of quorum sensing-based communications between bacteria and fungi.mBio · 2026Review
- Several plant self-incompatibility systems may be controlled by atypical receptor-ligand interactions.The Plant journal : for cell and molecular biology · 2026Review
- The rise and future of peptide-based antimicrobials.Journal of microbiology (Seoul, Korea) · 2026Review
- Approaches to deorphanize secretome: Classical, computational, and next generation strategies to reveal ligand-receptor networks.EXO : beyond the cell · 2026Article
- Assessment and applications of joint profiling of single-cell chromatin accessibility and transcriptome.Briefings in bioinformatics · 2025Review
- Engineered Proteins and Chemical Tools to Probe the Cell Surface Proteome.Chemical reviews · 2025Review
- Crystal structure of Isthmin-1 and reassessment of its functional role in pre-adipocyte signaling.Nature communications · 2025Article
- Emerging frontiers in protein structure prediction following the AlphaFold revolution.Journal of the Royal Society, Interface · 2025Review
- Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions.Molecular cell · 2025Article
- Article
- FlyPhoneDB2: A computational framework for analyzing cell-cell communication inComputational and structural biotechnology journal · 2025Article
- Investigating plasticity within the interleukin-6 family with AlphaFold-Multimer.Computational and structural biotechnology journal · 2025Article
- Leveraging coevolutionary insights and AI-based structural modeling to unravel receptor-peptide ligand-binding mechanisms.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer.bioRxiv : the preprint server for biology · 2024Article
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11 authors.
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Abstract
Secreted proteins play crucial roles in paracrine and endocrine signaling; however, identifying ligand-receptor interactions remains challenging. Here, we benchmarked AlphaFold2 (AF2) as a screening approach to identify extracellular ligands to single-pass transmembrane receptors. Key to the approach is the optimization of AF2 input and output for screening ligands against receptors to predict the most probable ligand-receptor interactions. The predictions were performed on ligand-receptor pairs not used for AF2 training. We demonstrate high discriminatory power and a success rate of close to 90% for known ligand-receptor pairs and 50% for a diverse set of experimentally validated interactions. Further, we show that screen accuracy does not correlate linearly with prediction of ligand-receptor interaction. These results demonstrate a proof of concept of a rapid and accurate screening platform to predict high-confidence cell-surface receptors for a diverse set of ligands by structural binding prediction, with potentially wide applicability for the understanding of cell-cell communication.
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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.