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首页> 外文期刊>Chemphyschem: A European journal of chemical physics and physical chemistry >Structure Determination of a Flexible Cyclic Peptide Based on NMR and MD Simulation 3J-Coupling
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Structure Determination of a Flexible Cyclic Peptide Based on NMR and MD Simulation 3J-Coupling

机译:基于NMR和MD模拟3J耦合的柔性环状肽的结构确定。

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Molecular dynamics (MD) simulations, in which experimental values such as nuclear Overhauser effects (NOEs), dipolar couplings, ~3J-coupling constants or crystallographic structure factors are used to bias the values of specific molecular properties towards experimental ones, are often carried out to study the structure refinement of peptides and proteins. However, 3Jcoupling constants are usually not employed because of the multiplicity of torsional angle values (q) corresponding to each 3J-coupling constant value. Here, we apply the method of adaptively enforced restraining using a local-elevation (LE) biasing potential energy function in which a memory function penalizes conformations in case both the average < 3J> and the current 3J-values deviate from the experimental target value. Then, the molecule is forced to sample other parts of the conformational space, thereby being able to cross high energy barriers and to bring the simulated average <3J> close to the measured < 3J> value. Herein, we show the applicability of this method in structure refinement of a cyclo-β-- tetrapeptide by enforcing the 3J-value restraining with LE on twelve backbone torsional angles. The resulting structural ensemble satisfies the experimental 3J-coupling data better than the NMR model structure derived using conventional singlestructure refinement based on these data. Thus, application of local-elevation search MD simulation in combination with biasing towards 3J-coupling makes it possible to use ~3J-couplings quantitatively in structure determination of peptides.
机译:经常进行分子动力学(MD)模拟,其中使用诸如核Overhauser效应(NOE),偶极耦合,〜3J耦合常数或晶体结构因子之类的实验值来将特定分子特性的值偏向实验值。研究肽和蛋白质的结构细化。然而,由于对应于每个3J耦合常数值的扭转角值(q)的多样性,通常不采用3J耦合常数。在这里,我们应用一种使用局部高程(LE)偏置势能函数的自适应强制约束方法,其中在平均值<3J>和当前3J值均偏离实验目标值的情况下,记忆函数会惩罚构象。然后,迫使分子对构象空间的其他部分进行采样,从而能够越过高能垒并使模拟平均值<3J>接近测量的<3J>值。在本文中,我们通过在12个骨架扭转角上用LE强制3J值约束来显示该方法在环β-四肽结构细化中的适用性。所得的结构集合比基于常规的单结构细化基于这些数据得出的NMR模型结构更好地满足了实验3J耦合数据。因此,结合使用局部高程搜索MD模拟和偏向3J耦合,可以在肽的结构确定中定量使用〜3J耦合。

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