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.