Protein–protein interactions (PPIs) are vital to all biological processes. These interactions are often dynamic, sometimes transient, typically occur over large topographically shallow protein surfaces, and can exhibit a broad range of affinities. Considerable progress has been made in determining PPI structures. However, given the above properties, understanding the key determinants of their thermodynamic stability remains a challenge in chemical biology. An improved ability to identify and engineer PPIs would advance understanding of biological mechanisms and mutant phenotypes and also provide a firmer foundation for inhibitor design. In silico prediction of PPI hot-spot amino acids using computational alanine scanning (CAS) offers a rapid approach for predicting key residues that drive protein–protein association. This can be applied to all known PPI structures; however there is a trade-off between throughput and accuracy. Here we describe a comparative analysis of multiple CAS methods, which highlights effective approaches to improve the accuracy of predicting hot-spot residues. Alongside this, we introduce a new method, BUDE Alanine Scanning, which can be applied to single structures from crystallography and to structural ensembles from NMR or molecular dynamics data. The comparative analyses facilitate accurate prediction of hot-spots that we validate experimentally with three diverse targets: NOXA-B/MCL-1 (an α-helix-mediated PPI), SIMS/SUMO, and GKAP/SHANK-PDZ (both β-strand-mediated interactions). Finally, the approach is applied to the accurate prediction of hot-spot residues at a topographically novel Affimer/BCL-xL protein–protein interface.

The principles of β-sheet folding and design for α-peptidic sequences are well established, while those for sheet mimetics containing homologated amino acid building blocks are still under investigation. To reveal the structure-function relations of β-amino-acid-containing foldamers, we followed a top-down approach to study a series of α/β-peptidic analogs of anginex, a β-sheet-forming antiangiogenic peptide. Eight anginex analogs were developed by systematic α → β(3) substitutions and analyzed by using NMR and CD spectroscopy. The foldamers retained the β-sheet tendency, though with a decreased folding propensity. β-Sheet formation could be induced by a micellar environment, similarly to that of the parent peptide. The destructuring effect was higher when the α → β(3) exchange was located in the β-sheet core. Analysis of the β-sheet stability versus substitution pattern and the local conformational bias of the bulky β(3)V and β(3)I residues revealed that a mismatch between the H-bonding preferences of the α- and β-residues played a minor role in the structure-breaking effect. Temperature-dependent CD and NMR measurements showed that the hydrophobic stabilization was scaled-down for the α/β-peptides. Analysis of the biological activity of the foldamer peptides showed that four anginex derivatives dose-dependently inhibited the proliferation of a mouse endothelial cell line. The α → β(3) substitution strategy applied in this work can be a useful approach to the construction of bioactive β-sheet mimetics with a reduced aggregation tendency and improved pharmacokinetic properties.

Protein–protein interactions stabilized by multiple separate hot spots are highly challenging targets for synthetic scaffolds. Surface‐mimetic foldamers bearing multiple recognition segments are promising candidate inhibitors. In this work, a modular bottom‐up approach is implemented by identifying short foldameric recognition segments that interact with the independent hot spots, and connecting them through dynamic covalent library (DCL) optimization. The independent hot spots of a model target (calmodulin) are mapped with hexameric β‐peptide helices using a pull‐down assay. Recognition segment hits are subjected to a target‐templated DCL ligation through thiol–disulfide exchange. The most potent derivative displays low nanomolar affinity towards calmodulin and effectively inhibits the calmodulin–TRPV1 interaction. The DCL assembly of the folded segments offers an efficient approach towards the de novo development of a high‐affinity inhibitor of protein–protein interactions.

Here we describe a comparative analysis of multiple CAS methods, which highlights effective approaches to improve the accuracy of predicting hot-spot residues. Alongside this, we introduce a new method, BUDE Alanine Scanning, which can be applied to single structures from crystallography, and to structural ensembles from NMR or molecular dynamics data. The comparative analyses facilitate accurate prediction of hot-spots that we validate experimentally with three diverse targets: NOXA-B/MCL-1 (an α helix-mediated PPI), SIMS/SUMO and GKAP/SHANK-PDZ (both β strand-mediated interactions). Finally, the approach is applied to the accurate prediction of hot-residues at a topographically novel Affimer/BCL-xL protein-protein interface.

Following a quantitative validation approach, we tested the AMBER ff03 and GAFF force fields with the TIP3P explicit water model in molecular dynamic simulations of β-peptide foldamers. The test sequences were selected to represent a wide range of folding behavior in water: compact helix, strand mimetic geometry, and the state of disorder. The combination AMBER ff03-TIP3P successfully predicted the experimentally observed conformational properties and reproduced the NOE distances and backbone (3)J coupling data at a good level. GAFF was unable to produce folded structures correctly due to its biased torsion potentials. We can recommend AMBER ff03-TIP3P for simulations involving β-peptide sequences in aqueous media including ordered and disordered structures.