These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
Metal_Cation_Binding_Mechanisms_of_Q_Proline_Peptoid_Macrocycles_in_Solution.pdf (2.97 MB)

Metal Cation-Binding Mechanisms of Q-Proline Peptoid Macrocycles in Solution

submitted on 13.01.2021, 13:54 and posted on 18.01.2021, 05:15 by Matthew Hurley, Justin Northrup, Yunhui Ge, Christian Schafmeister, Vincent Voelz
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 pre-organize 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. The BICePs approach circumvents the need for bespoke force field parameterization, instead relying on experimental restraints to help narrow the possible set of cis/trans amide isomers in solution. 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 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.


National Institutes of Health grant 1R01GM123296

National Science Foundation CNS-1625061

US Army Research Laboratory W911NF-16-2-0189

NIH S10-OD020095


Email Address of Submitting Author


Temple University


United States

ORCID For Submitting Author


Declaration of Conflict of Interest

no conflict of interest

Version Notes

version v1