9CDZ

Crystal Structure of MDM2-Peptide Complex

Summary for 9CDZ

• Entry DOI: 10.2210/pdb9cdz/pdb
• Descriptor: E3 ubiquitin-protein ligase Mdm2, Peptide, SODIUM ION, ... (4 entities in total)
• Functional Keywords: de novo design, cyclic peptide, deep learning, alphafold, mdm2, oncoprotein
• Biological source: Homo sapiens (human); More
• Total number of polymer chains: 4
• Total formula weight: 28340.14

Authors

Bera, A.K.,Rettie, S.,Bhardwaj, G. (deposition date: 2024-06-25, release date: 2025-04-16, Last modification date: 2025-06-18)

Primary citation

Rettie, S.A.,Campbell, K.V.,Bera, A.K.,Kang, A.,Kozlov, S.,Bueso, Y.F.,De La Cruz, J.,Ahlrichs, M.,Cheng, S.,Gerben, S.R.,Lamb, M.,Murray, A.,Adebomi, V.,Zhou, G.,DiMaio, F.,Ovchinnikov, S.,Bhardwaj, G.
Cyclic peptide structure prediction and design using AlphaFold2.
Nat Commun, 16:4730-4730, 2025

PubMed 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 < 1.0 Å), highlighting the atomic level accuracy in our approach. Further, we used the set of hallucinated peptides as starting scaffolds to design binders with nanomolar IC against MDM2 and Keap1. The computational methods and scaffolds developed here provide the basis for the custom design of peptides for diverse protein targets and therapeutic applications.

PubMed: 40399308
DOI: 10.1038/s41467-025-59940-7

Experimental method

X-RAY DIFFRACTION (1.72 Å)