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金属阳离子与 Q-脯氨酸类肽大环在溶液中的结合机制。

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

机构信息

Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States.

出版信息

J Chem Inf Model. 2021 Jun 28;61(6):2818-2828. doi: 10.1021/acs.jcim.1c00447. Epub 2021 Jun 14.

Abstract

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- amide conformation, whose formation is likely limited by the slow rate of / 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.

摘要

可折叠和功能化的肽模拟支架的合理设计需要综合应用计算和实验方法。最近,一类新的设计肽大环包含螺旋寡聚脯氨酸模拟物(Q-脯氨酸),当与单价金属阳离子结合时被发现会预组织。为了确定这些阳离子结合的大环在溶液中的结构,我们使用贝叶斯推断方法(BICePs)来协调增强采样分子模拟与实验 NMR 研究中的稀疏 ROESY 相关,以预测和设计大环的构象和结合特性,作为肽模拟物的功能支架。然后,模拟预测在溶液中最普遍存在的构象,在存在明确定位阳离子的情况下产生观察到结合事件的轨迹,揭示出高度预组织的全酰胺构象,其形成可能受到 / 异构化的缓慢速率限制。有趣的是,这种构象与在不存在阳离子的情况下解决的外消旋晶体结构不同。从距离相关的平均力势能中计算出的阳离子结合自由能表明,Na 对大环的亲和力高于 K,两种阳离子在乙腈中的结合强度都远高于水。模拟的亲和力能够正确地对不同大环序列在不同金属阳离子和溶剂存在下表现出的预组织程度进行排序,这表明我们的方法适用于溶液状态的计算设计。

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