Nuclear Magnetic Resonance (NMR1) spectroscopy is an important experimental technique that allows one to study protein structure in solution and to identify important sites in a protein. An important bottleneck in NMR protein structure determination is the assignment of NMR peaks to the correspond­ing nuclei. Structure-based assignment (SBA) aims to solve this problem with the help of a template protein which is homologous to the target and has applications in the study of structure-activity relationship, protein-protein and protein-ligand interactions. We formulate SBA as a linear assignment problem with additional Nuclear Overhauser Effect (NOE) constraints, which can be solved within Nuclear Vector Replacement's (NVR) ([7], [8]) framework. Our approach uses NVR's scoring function and data types, and also gives the option of using CH and NH RDCs, instead of NH RDCs which NVR requires. We test our technique on NVR's data set as well as on two new proteins. Our results are comparable to NVR's assignment accuracy on NVR's test set, but higher on novel proteins. Our approach allows partial assignments. It is also complete and can return the optimum as well as near-optimum assignments. Furthermore, it allows us to analyze the information content of each data type and is easily extendable to accept new forms of input data, such as additional RDCs.

中文翻译：

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NVR-BIP：使用二进制整数编程进行基于 NMR 结构分配的核向量替换

核磁共振 (NMR1) 光谱是一项重要的实验技术，可让人们研究溶液中的蛋白质结构并识别蛋白质中的重要位点。NMR 蛋白质结构测定的一个重要瓶颈是将 NMR 峰分配给相应的核。基于结构的分配（SBA）旨在借助与目标同源的模板蛋白来解决这一问题，并在结构-活性关系、蛋白质-蛋白质和蛋白质-配体相互作用的研究中得到应用。我们将 SBA 表述为具有附加核奥豪瑟效应 (NOE) 约束的线性分配问题，可以在核矢量替换 (NVR) ([7], [8]) 框架内解决。我们的方法使用 NVR 的评分函数和数据类型，并且还提供使用 CH 和 NH RDC 的选项，而不是 NVR 所需的 NH RDC。我们在 NVR 的数据集以及两种新蛋白质上测试了我们的技术。我们的结果与 NVR 在 NVR 测试集上的分配准确性相当，但在新型蛋白质上更高。我们的方法允许部分分配。它也是完整的，可以返回最佳和接近最佳的分配。此外，它允许我们分析每种数据类型的信息内容，并且可以轻松扩展以接受新形式的输入数据，例如附加的 RDC。