articleNature CommunicationsMay 21, 2025GOLD OA

Cyclic peptide structure prediction and design using AlphaFold2

University of Washington · Massachusetts Institute of Technology · +2 more institutions

PubMed
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Abstract

Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here, we introduce AfCycDesign, a deep learning approach for accurate structure prediction, sequence redesign, and de novo hallucination of cyclic peptides. Using AfCycDesign, we identified over 10,000 structurally-diverse designs predicted to fold into the designed structures with high confidence. X-ray crystal structures for eight tested de novo designed sequences match very closely with the design models (RMSD

Citation impact

51
total citations
FWCI
31.60
Percentile
100%
References
57
Citations per year

Authors

17

Topics & keywords

Keywords
  • Peptide
  • Computational biology
  • Computer science
  • Biology
  • Biochemistry
UN Sustainable Development Goals
  • Zero hunger
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