MetaD simulations rationalize the conformational effects induced by N-methylation of RGD cyclohexapeptides

Cyclic peptides are a promising class of compounds that can be used as therapeutics in modulation of protein-protein interactions thanks to their favourable pharmacokinetic characteristics. Nevertheless their application has been relatively limited due to the difficulties to accurately predict in silico their three-dimensional structure and their inhibitory activity. Because of these challenges, their optimization for specific biological targets has been mainly based on empirical approaches, requiring massive time-consuming synthesis campaigns of different variants to identify sets of molecules with appropriate conformational and target-binding properties. Computational tools could be fundamental in accelerating the drug design process, thus reducing the efforts dedicated to expensive and time consuming compound synthesis In this scenario a detailed conformational search of ligands followed by docking calculations is highly recommendable to achieve reliable computational predictability. We have developed a multi-stage computational protocol[1] able i. to reliably predict the affinity of a set of cyclic-peptides towards different integrins, ii. to rationalize the interplay between conformational equilibria and receptor affinity. This protocol relies on the combination of enhanced sampling molecular dynamics technique (Bias Exchange Metadynamics, BE-META), docking calculations and re-scoring via Molecular Mechanics/Generalized Born Surface Area methods. We have explored the applicability and reliability of our method investigating the impact of single and multiple N-methylation on the equilibrium conformations of five head-to-tail cyclic RGD (Arg-Gly-Asp) hexapeptides that were generated to increase their selectivity towards \u3b1IIb\u3b23 integrin.[2] We obtained excellent results: we validated the conformational sampling obtaining a good agreement with available NMR data and demonstrated our prediction ability discriminating between binders and non-binders. Herein we have shown that BE-META can represent a promising in silico spatial screening strategy to predict the conformational effects of N-methylation in cyclic-peptides, opening new perspectives in their application as therapeutic inhibitors of protein-protein interactions. Moreover our results are relevant in the field of integrin-targeting RGD peptidomimetics, as they offer a structural rationale for why N-methylation increases peptides affinities towards a specific integrin. We expect that this combination of techniques will be successfully exploited in future to predict the conformational effects of methylation also in other classes of cyclopeptides. Herein, the method could be easily extended to predict the conformational effect of other chemical modifications, of flanking residues or of d-amino acids. Such an approach may be well exploited before entering time-consuming chemical synthesis and binding experiments