The
rational design of foldable and functionalizable peptidomimetic
scaffolds requires the concerted application of both computational
and experimental methods. Recently, a new class of designed peptoid
macrocycle incorporating spiroligomer proline mimics (Q-prolines)
has been found to preorganize when bound by monovalent metal cations.
To determine the solution-state structure of these cation-bound macrocycles,
we employ a Bayesian inference method (BICePs) to reconcile enhanced-sampling
molecular simulations with sparse ROESY correlations from experimental
NMR studies to predict and design conformational and binding properties
of macrocycles as functional scaffolds for peptidomimetics. Conformations
predicted to be most populated in solution were then simulated in
the presence of explicit cations to yield trajectories with observed
binding events, revealing a highly preorganized all-trans amide conformation, whose formation is likely limited by the slow
rate of cis/trans isomerization.
Interestingly, this conformation differs from a racemic crystal structure
solved in the absence of cation. Free energies of cation binding computed
from distance-dependent potentials of mean force suggest Na+ has a higher affinity to the macrocycle than K+, with
both cations binding much more strongly in acetonitrile than water.
The simulated affinities are able to correctly rank the extent to
which different macrocycle sequences exhibit preorganization in the
presence of different metal cations and solvents, suggesting our approach
is suitable for solution-state computational design.