Protein-protein interactions (PPIs) are involved in many biological pathways. Dysregulated PPIs are associated with numerous diseases, thus making them important therapeutic targets. More than 7,000 “hot loops” have been identified at PPI interfaces and these hot loops are well-suited to mimic with cyclic peptides. Compared to small molecules, cyclic peptides can bind the large, flat surfaces associated with PPIs with high potency and specificity, and could be used as potential PPI inhibitors. In this work, a computational strategy to develop cyclic-peptide inhibitors for PPIs is proposed. Specifically, we first determined the size of the cyclic peptides that are best at mimicking a hot loop by comparing the hot loop backbone conformation to those observed in cyclic peptide simulations. Then, using a scoring function which estimates the structural preferences of neighboring residues in a cyclic peptide of a given size, the hot loop is connected with designed amino acids that best pre-organize the hot spot residues to mimic the bioactive bound state to form a cyclic peptide. Finally, an enhanced sampling method that is able to efficiently sample the possible conformations of a cyclic peptide is used to verify that the designed cyclic peptides are indeed well-structured and adopt the desired conformation.

Designing cyclic-peptide inhibitors of protein-protein interactions by mimicking hot loops

256th National Meeting (2018)

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