Damberg Charlotta S, Orekhov Vladislav Yu, Billeter Martin
Swedish NMR Centre, Göteborg University, Sweden.
J Med Chem. 2002 Dec 19;45(26):5649-54. doi: 10.1021/jm020866a.
Drug discovery procedures based on NMR typically require the analysis of thousands of NMR spectra. For example, in "SAR by NMR", two-dimensional NMR spectra are recorded for a target protein mixed with ligand candidates from a comprehensive library of small molecules and are compared to the corresponding spectrum for the protein alone. We present an automated procedure for the comparative analysis of large sets of heteronuclear single quantum coherence spectra, which is based on three-way decomposition and implemented as the software package MUNIN. In a single step, spectra with differences in the peak positions (indicating ligand binding) and the affected peaks are identified. By omission of peak picking, ad hoc scoring of the quality of doubtful peaks is avoided. The procedure has been tested on the bacterial ribonuclease barnase, with a protein concentration of only 50 microM, using several small molecules including the substrate analogue 3'-GMP. Sets of 51 spectra were processed simultaneously, and it is concluded that spectra with binding ligands can be unambiguously identified from much larger sets of spectra.
基于核磁共振（NMR）的药物发现程序通常需要分析数千个NMR谱。例如，在“基于NMR的构效关系研究（SAR by NMR）”中，会为目标蛋白与来自小分子综合文库的候选配体混合物记录二维NMR谱，并与仅该蛋白的相应谱进行比较。我们提出了一种用于大量异核单量子相干谱比较分析的自动化程序，该程序基于三向分解，并作为软件包MUNIN实现。在单个步骤中，可识别出峰位置存在差异（表明配体结合）的谱以及受影响的峰。通过省略峰挑选，避免了对可疑峰质量进行临时评分。该程序已在细菌核糖核酸酶巴那斯酶上进行了测试，蛋白浓度仅为50微摩尔，使用了包括底物类似物3'-GMP在内的几种小分子。同时处理了51个谱的集合，得出的结论是，从大得多的谱集中可以明确识别出带有结合配体的谱。
