Deep Alanine Scanning Reveals Potent Multi-alanine-substituted Protein–protein Interaction Inhibitors

Abstract

Establishing structure–activity relationships is crucial to understand and optimize the activity of peptide-based inhibitors of protein–protein interactions. Single alanine mutagenesis provides limited information toward this goal. To guide multiple simultaneous peptide modifications with retention of biological activity, we used synthetic combinatorial alanine-scanning libraries—in which each position was varied with either the wild type residue or alanine—with an affinity selection platform to study the mutational tolerance of protein–ligand interactions. Applying this platform to a peptide binder to the oncogenic protein MDM2, several multi-alanine-substituted analogs that retained low nanomolar affinity were discovered, including a 13-mer binder with seven alanine substitutions at non-hotspot positions. These binders served as templates for further modifications, generating cysteine-substituted, perfluoroaryl-stapled peptides with sub-nanomolar affinity and ten-fold improved proteolytic stability. The alanine substitution tolerances for peptide ligands of the 12ca5 antibody and 14-3-3 regulatory protein were also reported, demonstrating the general applicability of this new platform. We envision that deep combinatorial alanine scanning will be a powerful tool for structure–activity optimization of potential peptide therapeutics.

Rapid de novo discovery of peptidomimetic affinity reagents for human angiotensin converting enzyme 2

“…Thus, discovery efforts with AS-MS have generally been limited to small combinatorial libraries (10 3 -10 6 members), which were biased toward the target protein in a 'focused' or structure-based manner 38,39 . AS-MS of these focused libraries remains a reliable way to rapidly identify key binding 'hot-spot' residues and combinatorically introduce noncanonical amino acids 38,40,41 . Recent advancements made by our group in the MS/MS sequencing of complex peptidomimetic mixtures 42 and optimized AS-MS selection conditions 43 have enabled de novo discovery of high affinity binders from fully randomized peptidomimetic libraries up to 10 8 members 43 .…”