ArticleNature chemical biology2025
Accurate de novo design of high-affinity protein-binding macrocycles using deep learning.
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Article in Nature chemical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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37citing papers in PubMed
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37 citing papers in PubMed.
- Artificial intelligence-assisted design of self-assembling peptide hydrogels for neural regeneration: Principles and opportunities.Bioactive materials · 2027Review
- Peptide Aptamers: Innovative Design and Applications in Pathogen Detection.Chembiochem : a European journal of chemical biology · 2026Review
- Molecular dockingDigital discovery · 2026Article
- HighFold4: extending AlphaFold3 to accurate cyclic peptide conformation prediction via custom chemical connectivity.Briefings in bioinformatics · 2026Article
- Enhancing De Novo Designed Peptides and Proteins via Irreversible Covalent Isoquinolinium Capture.ACS chemical biology · 2026Article
- A Unified Hierarchical Multiscale Fusion Framework for Drug-Target Affinity Prediction: From Benchmark Performance to Nanomolar Inhibitor Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- HFGuidedDesign:Chemical science · 2026Article
- Cyclic Peptides in Modern Drug Discovery: Trends and Therapeutic Directions.Journal of medicinal chemistry · 2026Review
- AI Designed Conformation Locking Peptides Target STING to Restore Diabetic Wound Healing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Peptides as programmable molecular scaffolds: from chemical synthesis and engineering to translational medicine.RSC chemical biology · 2026Review
- Cyclic Peptides as Modulators of Protein-Protein Interactions: A Survival Guide from Discovery Platforms to AI-Driven Design.International journal of molecular sciences · 2026Review
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- Tools For Building Artificial Biological Nanostructures.ACS nano · 2026Review
- Protein design and RNA design: Perspectives.Quantitative biology (Beijing, China) · 2026Article
- Design of permeability-optimized target-binding macrocyclesChemical science · 2026Article
- Breaking the bonds: targeting protein dimerization for prostate cancer therapy.Endocrinology · 2026Review
- A Comparative Review of Artificial Intelligence Applications in Small Molecule Versus Peptide Drug Discovery.International journal of molecular sciences · 2026Review
- Fast Generation of Simulation-Quality Structural Ensembles of Mixed-Chirality Cyclic Peptides via Diffusion Models.Journal of chemical theory and computation · 2026Article
- Peptide-functionalized nanoparticles for brain-targeted therapeutics.Drug delivery and translational research · 2026Review
- Macrocyclic Molecular Glues for the 14-3-3/ChREBP Interaction: Affinity and Cooperativity in an Inverse Relationship.Angewandte Chemie (International ed. in English) · 2026Article
Corrections and comments
- Update ofAccurate2024
Authors and funding
26 authors.
Stephen A Rettie *Department of Medicinal Chemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-9797-6939
David Juergens *Institute for Protein Design, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-6425-8391
Victor Adebomi *Department of Medicinal Chemistry, University of Washington, Seattle, WA, USA.
Yensi Flores BuesoDepartment of Medicinal Chemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-2118-2195
Qinqin ZhaoDepartment of Microbiology, University of Washington, Seattle, WA, USA.
Alexandria N LeveilleDepartment of Chemistry, Tufts University, 62 Talbot Avenue, Medford, MA, USA.
Andi LiuDepartment of Microbiology, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-8795-9614
Asim K BeraInstitute for Protein Design, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-9473-2912
Joana A WilmsHeinrich-Heine-Universität Düsseldorf, Institut für Physikalische Biologie, Düsseldorf, Germany.ORCID http://orcid.org/0000-0001-5655-7009
Alina ÜffingHeinrich-Heine-Universität Düsseldorf, Institut für Physikalische Biologie, Düsseldorf, Germany.ORCID http://orcid.org/0000-0001-8808-1033
Alex KangInstitute for Protein Design, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-5487-0499
Evans BrackenbroughInstitute for Protein Design, University of Washington, Seattle, WA, USA.
Mila LambInstitute for Protein Design, University of Washington, Seattle, WA, USA.
Stacey R GerbenInstitute for Protein Design, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-0313-6248
Analisa MurrayInstitute for Protein Design, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-1560-6673
Paul M LevineInstitute for Protein Design, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-4874-5557
Maika SchneiderDepartment of Medicinal Chemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0009-0006-9798-852X
Vibha VasireddyDepartment of Medicinal Chemistry, University of Washington, Seattle, WA, USA.
Sergey OvchinnikovDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Oliver H WeiergräberForschungszentrum Jülich, Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Jülich, Germany.
Dieter WillboldHeinrich-Heine-Universität Düsseldorf, Institut für Physikalische Biologie, Düsseldorf, Germany.ORCID http://orcid.org/0000-0002-0065-7366
Joshua A KritzerDepartment of Chemistry, Tufts University, 62 Talbot Avenue, Medford, MA, USA.ORCID http://orcid.org/0000-0003-2878-6781
Joseph D MougousDepartment of Microbiology, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-5417-4861
David BakerInstitute for Protein Design, University of Washington, Seattle, WA, USA. dabaker@uw.edu.ORCID http://orcid.org/0000-0001-7896-6217
Frank DiMaioInstitute for Protein Design, University of Washington, Seattle, WA, USA. dimaio@uw.edu.ORCID http://orcid.org/0000-0002-7524-8938
Gaurav BhardwajDepartment of Medicinal Chemistry, University of Washington, Seattle, WA, USA. gauravb@uw.edu.ORCID http://orcid.org/0000-0001-6554-2335
Funding
X-ray Scattering Technology CoreP30GM133893 · NIGMS · BROOKHAVEN SCIENCE ASSOC-BROOKHAVEN LAB · PI Vivian Stojanoff · 2019 to 2026
$38.6MDe Novo Design of Minibinder Antagonists for COVID-19 and Future PandemicsR01AI160052 · NIAID · UNIVERSITY OF WASHINGTON · PI BAKER, DAVID, FULLER, DEBORAH H. · 2021 to 2025
$3.5MDiversity Supplement for Imani McDonald - Developing Autophagy-Targeting Chimeras and Optimizing Cell Penetration of Large-Molecule TherapeuticsR35GM148407 · NIGMS · TUFTS UNIVERSITY MEDFORD · PI Joshua A Kritzer · 2023 to 2026
$2.6MComputational de novo design of macrocyclic type I Signal Peptidase inhibitorsR21AI178088 · NIAID · UNIVERSITY OF WASHINGTON · PI BHARDWAJ, GAURAV · 2024 to 2025
$412kBill and Melinda Gates Foundation (Bill & Melinda Gates Foundation) GR047983Deutsche Forschungsgemeinschaft (German Research Foundation) 267205415-SFB 1208NIAID NIH HHS R01 AI160052NIAID NIH HHS R21 AI178088NIGMS NIH HHS P30 GM133893NIGMS NIH HHS R35 GM148407United States Department of Defense | Defense Advanced Research Projects Agency (DARPA) HR001120S0052United States Department of Defense | Defense Advanced Research Projects Agency (DARPA) HR0011-21-2-0012United States Department of Defense | Defense Threat Reduction Agency (DTRA) HDTRA1-19-1-0003U.S. Department of Health & Human Services | National Institutes of Health (NIH) GM148407U.S. Department of Health & Human Services | National Institutes of Health (NIH) R0AI160052
Abstract
Developing macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource intensive and provide little control over binding mode. Despite progress in protein design, there are currently no robust approaches for de novo design of protein-binding macrocycles. Here we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic binders against protein targets of interest. We tested 20 or fewer designed macrocycles against each of four diverse proteins and obtained binders with medium to high affinity against all targets. For one of the targets, Rhombotarget A (RbtA), we designed a high-affinity binder (K
Indexed as
Deep LearningDrug DesignMacrocyclic CompoundsBinding SitesCrystallography, X-RayHumansModels, MolecularProtein BindingMacrocyclic Compounds
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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.