Elucidating the inhibition of peptidoglycan biosynthesis in Staphylococcus aureus by albocycline, a macrolactone isolated from Streptomyces maizeus

Liang, Hai; Zhou, Guangfeng; Ge, Yunhui; D'Ambrosio, Elizabeth A.; Eidem, Tess M.; Blanchard, Catlyn; Shehatou, Cindy; Chatare, Vijay K.; Dunman, Paul M.; Valentine, Ann M.; Voelz, Vincent A.; Grimes, Catherine L.; Andrade, Rodrigo

doi:10.1016/j.bmc.2018.05.017

Cited by 20 publications

(19 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The output of BICePs is a set of refined conformational populations optimally consistent with both experiment and theory. BICePs has previously been used to successfully infer conformational populations of macrolides, 51,60 peptide macrocycles 23 and peptoid foldamers. 15 61 Briefly, BICePs is a Bayesian inference method applied to a set of discrete conformational states X.…”

Section: Bayesian Inference Of Conformational Populations (Biceps)mentioning

confidence: 99%

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

Hurley¹,

Northrup²,

Ge³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

<div>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.</div>

show abstract

Section: Bayesian Inference Of Conformational Populations (Biceps)mentioning

confidence: 99%

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

Hurley¹,

Northrup²,

Ge³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The output of BICePs is a set of refined conformational populations optimally consistent with both experiment and theory. BICePs has previously been used to successfully infer conformational populations of macrolides, 52,62 peptide macrocycles, 24 and peptoid foldamers. 16,63 Briefly, BICePs is a Bayesian inference method applied to a set of discrete conformational states X.…”

Section: ■ Methods and Resultsmentioning

confidence: 99%

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

Hurley

Northrup

et al. 2021

J. Chem. Inf. Model.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…The most probable values of σ can be obtained by the marginal distribution P(σ |D) = P(X, σ |D)dX, and the state populations are estimated as P(X|D) = P(X, σ |D)dσ (Figure 1). FIGURE 1 | An example of BICePs output for albocycline (Liang et al, 2018). (A) A comparison of conformational state populations p i (exp) inferred using only experimental restraints, vs. BICePs populations p i (sim + exp) inferred using a combination of the simulation-based prior and experimental restraints.…”

Section: Sampling the Posterior Using Mcmcmentioning

confidence: 99%

“… An example of BICePs output for albocycline (Liang et al, 2018 ). (A) A comparison of conformational state populations p i (exp) inferred using only experimental restraints, vs. BICePs populations p i (sim + exp) inferred using a combination of the simulation-based prior and experimental restraints.…”

Section: Theorymentioning

confidence: 99%

“…In subsequent work, BICePs predicted a similar (nearly equal) mixture of solution-state populations for albocycline, using 12 NOE distance restraints and seven dihedral restraints from

coupling constants (Chatare and Andrade, 2017 ). This information helped inform molecular simulation and computational docking studies of albocycline binding to MurA, an enzyme involved in peptidoglycan biosynthesis, a potential new target for Methicillin-resistant Staphylococcus aureus (MRSA) infection (Liang et al, 2018 ).…”

Section: Applications Of Bicepsmentioning

confidence: 99%

See 1 more Smart Citation

Reconciling Simulations and Experiments With BICePs: A Review

Voelz

Raddi

2021

Front. Mol. Biosci.

Self Cite

View full text Add to dashboard Cite

Bayesian Inference of Conformational Populations (BICePs) is an algorithm developed to reconcile simulated ensembles with sparse experimental measurements. The Bayesian framework of BICePs enables population reweighting as a post-simulation processing step, with several advantages over existing methods, including the proper use of reference potentials, and the estimation of a Bayes factor-like quantity called the BICePs score for model selection. Here, we summarize the theory underlying this method in context with related algorithms, review the history of BICePs applications to date, and discuss current shortcomings along with future plans for improvement.

show abstract

Elucidating the inhibition of peptidoglycan biosynthesis in Staphylococcus aureus by albocycline, a macrolactone isolated from Streptomyces maizeus

Cited by 20 publications

References 50 publications

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

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

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

Reconciling Simulations and Experiments With BICePs: A Review

Contact Info

Product

Resources

About