Abstract

Hydrocarbon-stapled peptides are a class of bioactive α-helical ligands developed to target protein-protein interactions. Peptide stapling has benefited from the development of several chemical reactions to modulate their membrane permeability and binding affinity. However, in most current programs, choosing the best stapling positions is usually a trial-and-error process. Here, we develop a protocol to obtain optimal stapling positions computationally. Our method is based on molecular dynamics simulations and free energy calculations with nonequilibrium approaches; here, we predict the binding poses, hot-spot residues, and binding affinity differences of a set of perfluoroarene stapled α-helical peptides of the BIM BH3 peptide to the BCLXL receptor. The prediction of the hot-spot residues within the target peptide through computational alanine scanning anticipates not only the key residues for the receptor-peptide complex formation but also which positions should be avoided when applying the stapling groups. The staple moieties introduce local conformational changes not only in the replaced positions but also on their neighbor residues of the template peptide further affecting their binding behavior. Our approach is successful at rank-ordering the binding affinities of these stapled peptides with respect to the BIM BH3 peptide.

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