Computational techniques predict the effects induced by N-methylation of RGD-cyclopeptides on integrin affinity

Cyclopeptides are a promising class of compounds for inhibiting protein-protein interactions. In particular, they provide opportunities to increase molecular size and interactions, constraining ligands into pre-organized bioactive conformations. This strategy is extremely successful in the field of integrin inhibitors, where the high receptor affinity and selectivity displayed by RGD cyclopeptides has been mainly ascribed to their pre-organization in solution. Nevertheless, the difficulties to accurately predict the three-dimensional structure and the inhibitory activity of cyclopeptides have limited their application, requiring expensive and time-consuming synthesis campaigns for their optimization. Computational tools could be fundamental in accelerating the drug design process. In this work we present a computational protocol[1] able to: i. predict the affinity of a set of cyclopeptides towards different integrins, ii. rationalize the interplay between conformational equilibria and receptor affinity. This protocol relies on a detailed conformational search of ligands, performed with an enhanced sampling molecular dynamic technique, followed by docking calculations. We have demonstrated the reliability of our method investigating the impact of single/multiple N-methylation on the equilibrium conformations of five RGD cyclopeptides, generated to increase their selectivity for αIIbβ3 integrin.[2] Therefore this protocol can represent a promising approach for in silico spatial screening. We expect that this combination of techniques will be successfully exploited in future to predict the conformational effects of methylations, other chemical modifications and flanking residues in cyclopeptides. Such an approach may be well exploited before entering time-consuming chemical synthesis and binding experiments.