Department of Chemistry, Physical & Theoretical Chemistry Laboratory, University of Oxford , South Parks Road, Oxford, Oxfordshire OX1 3QZ, U.K.
ZoBio BV , BioPartner 2 building, J.H. Oortweg 19, 2333 CH Leiden, The Netherlands.
J Am Chem Soc. 2017 Jul 19;139(28):9523-9533. doi: 10.1021/jacs.6b11358. Epub 2017 Jul 10.
Methyl groups are powerful probes for the analysis of structure, dynamics and function of supramolecular assemblies, using both solution- and solid-state NMR. Widespread application of the methodology has been limited due to the challenges associated with assigning spectral resonances to specific locations within a biomolecule. Here, we present Methyl Assignment by Graph Matching (MAGMA), for the automatic assignment of methyl resonances. A graph matching protocol examines all possibilities for each resonance in order to determine an exact assignment that includes a complete description of any ambiguity. MAGMA gives 100% accuracy in confident assignments when tested against both synthetic data, and 9 cross-validated examples using both solution- and solid-state NMR data. We show that this remarkable accuracy enables a user to distinguish between alternative protein structures. In a drug discovery application on HSP90, we show the method can rapidly and efficiently distinguish between possible ligand binding modes. By providing an exact and robust solution to methyl resonance assignment, MAGMA can facilitate significantly accelerated studies of supramolecular machines using methyl-based NMR spectroscopy.
甲基基团是分析超分子组装结构、动态和功能的有力探针，可同时用于溶液和固态 NMR 研究。由于在生物分子中对特定位置的光谱共振进行分配的相关挑战，该方法的广泛应用受到限制。在这里，我们提出了基于图匹配的甲基分配（MAGMA），用于甲基共振的自动分配。图匹配协议检查每个共振的所有可能性，以确定一个包含任何歧义的完整描述的精确分配。当 MAGMA 针对合成数据和使用溶液和固态 NMR 数据的 9 个交叉验证示例进行测试时，在有信心的分配中达到了 100%的准确性。我们表明，这种出色的准确性可以使用户能够区分蛋白质结构的替代形式。在 HSP90 的药物发现应用中，我们表明该方法可以快速有效地区分可能的配体结合模式。通过为甲基共振分配提供准确且稳健的解决方案，MAGMA 可以促进使用基于甲基的 NMR 光谱学对超分子机器的加速研究。
