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使用无 TOCSY 数据的 RDC 定义骨架进行蛋白质侧链共振分配和 NOE 分配。

Protein side-chain resonance assignment and NOE assignment using RDC-defined backbones without TOCSY data.

机构信息

Department of Computer Science, Duke University, Durham, NC 27708, USA.

出版信息

J Biomol NMR. 2011 Aug;50(4):371-95. doi: 10.1007/s10858-011-9522-4. Epub 2011 Jun 25.

Abstract

One bottleneck in NMR structure determination lies in the laborious and time-consuming process of side-chain resonance and NOE assignments. Compared to the well-studied backbone resonance assignment problem, automated side-chain resonance and NOE assignments are relatively less explored. Most NOE assignment algorithms require nearly complete side-chain resonance assignments from a series of through-bond experiments such as HCCH-TOCSY or HCCCONH. Unfortunately, these TOCSY experiments perform poorly on large proteins. To overcome this deficiency, we present a novel algorithm, called NASCA: (NOE Assignment and Side-Chain Assignment), to automate both side-chain resonance and NOE assignments and to perform high-resolution protein structure determination in the absence of any explicit through-bond experiment to facilitate side-chain resonance assignment, such as HCCH-TOCSY. After casting the assignment problem into a Markov Random Field (MRF), NASCA: extends and applies combinatorial protein design algorithms to compute optimal assignments that best interpret the NMR data. The MRF captures the contact map information of the protein derived from NOESY spectra, exploits the backbone structural information determined by RDCs, and considers all possible side-chain rotamers. The complexity of the combinatorial search is reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. Then an A* search algorithm is employed to find a set of optimal side-chain resonance assignments that best fit the NMR data. These side-chain resonance assignments are then used to resolve the NOE assignment ambiguity and compute high-resolution protein structures. Tests on five proteins show that NASCA: assigns resonances for more than 90% of side-chain protons, and achieves about 80% correct assignments. The final structures computed using the NOE distance restraints assigned by NASCA: have backbone RMSD 0.8-1.5 Å from the reference structures determined by traditional NMR approaches.

摘要

NMR 结构测定中的一个瓶颈在于侧链共振和 NOE 分配的繁琐和耗时过程。与研究充分的骨架共振分配问题相比,自动化的侧链共振和 NOE 分配相对较少被探索。大多数 NOE 分配算法需要从一系列通过键实验(如 HCCH-TOCSY 或 HCCCONH)中获得近乎完整的侧链共振分配。不幸的是,这些 TOCSY 实验在大型蛋白质上表现不佳。为了克服这一缺陷,我们提出了一种新的算法,称为 NASCA:(NOE 分配和侧链分配),以自动化侧链共振和 NOE 分配,并在没有任何明确的通过键实验(如 HCCH-TOCSY)来促进侧链共振分配的情况下进行高分辨率蛋白质结构测定。在将分配问题转化为马尔可夫随机场(MRF)之后,NASCA:扩展并应用组合蛋白质设计算法来计算最佳分配,以最佳地解释 NMR 数据。MRF 捕获了来自 NOESY 光谱的蛋白质的接触图信息,利用了由 RDCs 确定的骨架结构信息,并考虑了所有可能的侧链构象。通过使用死端消除(DEE)算法来减少组合搜索的复杂性,该算法修剪了可证明不是最佳解决方案一部分的侧链共振分配。然后使用 A*搜索算法找到一组最佳的侧链共振分配,以最佳地拟合 NMR 数据。然后使用这些侧链共振分配来解决 NOE 分配歧义并计算高分辨率蛋白质结构。对五个蛋白质的测试表明,NASCA:为超过 90%的侧链质子分配了共振,并实现了约 80%的正确分配。使用 NASCA:分配的 NOE 距离约束计算得到的最终结构的骨架 RMSD 与通过传统 NMR 方法确定的参考结构相差 0.8-1.5Å。

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