Scoring Conformational Metastability of Macrocyclic Peptides with Binding Pose Metadynamics

Potency optimization of macrocyclic peptides can include both modifying intermolecular interactions and modifying the conformational stability of the bioactive conformation. However, the number of possible modifications is vast. To identify modifications that enhance the stability of the binding conformations in a cost-effective manner, there is a need for a high-throughput in-silico method that scores the conformational stability of these modified molecules. For the common case where a binding conformation of a similar compound is known, the relative stability of this conformation for a series of compounds can theoretically be estimated by modeling the metastability of the bound state via conformational sampling techniques. Herein, we survey several sampling methods and report solution-state binding pose metadynamics as the most efficient of such sampling methods. In this manuscript, we compare both estimations of metastability from shorter solution-state sampling methods to both experimental affinities and more rigorous sampling methods to properly isolate the conformational effect on potency. In our benchmark calculations on macrocyclic peptide data sets where chemical modifications can be expected to influence the stability of the binding pose, our solution-state binding pose metadynamics workflow, which estimates conformational metastability of the bioactive state, agrees with more rigorous REST2 simulations while using significantly less computational resources. Further, for both the cases where REST2 simulations converge, as well as some others, the binding pose metadynamics metastability estimations correlated well with experimentally measured potencies, suggesting binding pose metadynamics may be an efficient method for quickly estimating the effect of binding pose metastability on potency.