We developed a cyclic peptide complex offset to enable the structural prediction of target proteins and cyclic peptide complexes and found AlphaFold2 with a cyclic peptide complex offset can predict structures with high accuracy. We also applied the cyclic peptide complex offset to the binder hallucination protocol of AfDesign, a de novo protein design method using AlphaFold, and we could design a high predicted local-distance difference test and lower separated binding energy per unit interface area than the native MDM2/p53 structure. Furthermore, the method was applied to 12 other protein-peptide complexes and one protein-protein complex. Our approach shows that it is possible to design putative cyclic peptide sequences targeting PPI.

Solubility-Aware Protein Binding Peptide Design Using AlphaFold

Introduction to the PyPI registration procedure for Python packages, using the example of QEPPI development to PyPI registration

Quantitative estimate of protein-protein interaction targeting drug-likeness

Development of a Quantitative Estimate Index for Early-Stage Screening of Compounds Targeting Protein-Protein Interactions