Des3PI: a fragment-based approach to design cyclic peptides targeting protein-protein interactions

Protein-protein interactions (PPIs) play crucial roles in many cellular processes and their deregulation often leads to cellular dysfunctions. One promising way to modulate PPIs is to use peptide derivatives that bind their protein target with high affinity and high specificity. Peptide modulators are often designed using secondary structure mimics. However, fragment-based design is an alternative emergent approach in the PPI field. Most of the reported computational fragment-based libraries targeting PPIs are composed of small molecules or already approved drugs, but, according to our knowledge, no amino acid based library has been reported yet. In this context, we developed a novel fragment-based approach called Des3PI (design of peptides targeting protein-protein interactions) with a library composed of natural amino acids. All the amino acids are docked into the target surface using Autodock Vina. The resulting binding modes are geometrically clustered, and, in each cluster, the most recurrent amino acids are identified and form the hotspots that will compose the designed peptide. This approach was applied on Ras and Mcl-1 proteins, as well as on A[Formula: see text] protofibril. For each target, at least five peptides generated by Des3PI were tested in silico: the peptides were first blindly docked on their target, and then, the stability of the successfully docked complexes was verified using 200 ns MD simulations. Des3PI shows very encouraging results by yielding at least 3 peptides for each protein target that succeeded in passing the two-step assessment.