Constantine Keith L, Davis Malcolm E, Metzler William J, Mueller Luciano, Claus Brian L
Bristol Myers Squibb Pharmaceutical Research Institute, P.O. Box 4000, Princeton, New Jersey 08543, USA.
J Am Chem Soc. 2006 Jun 7;128(22):7252-63. doi: 10.1021/ja060356w.
Given the three-dimensional (3D) structure of a protein, the binding pose of a ligand can be determined using distance restraints derived from assigned intra-ligand and protein-ligand nuclear Overhauser effects (NOEs). A primary limitation of this approach is the need for resonance assignments of the ligand-bound protein. We have developed an approach that utilizes data from 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectra for evaluating ligand binding poses without requiring protein NMR resonance assignments. Only the 1H NMR assignments of the bound ligand are essential. Trial ligand binding poses are generated by any suitable method (e.g., computational docking). For each trial binding pose, the 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectrum is predicted, and the predicted and observed patterns of protein-ligand NOEs are matched and scored using a fast, deterministic bipartite graph matching algorithm. The best scoring (lowest "cost") poses are identified. Our method can incorporate any explicit restraints or protein assignment data that are available, and many extensions of the basic procedure are feasible. Only a single sample is required, and the method can be applied to both slowly and rapidly exchanging ligands. The method was applied to three test cases: one complex involving muscle fatty acid-binding protein (mFABP) and two complexes involving the leukocyte function-associated antigen 1 (LFA-1) I-domain. Without using experimental protein NMR assignments, the method identified the known binding poses with good accuracy. The addition of experimental protein NMR assignments improves the results. Our "NOE matching" approach is expected to be widely applicable; i.e., it does not appear to depend on a fortuitous distribution of binding pocket residues.
给定蛋白质的三维（3D）结构，可以使用源自配体内和蛋白质 - 配体核Overhauser效应（NOE）的距离约束来确定配体的结合构象。这种方法的一个主要限制是需要对配体结合蛋白进行共振归属。我们开发了一种方法，该方法利用来自3D 13C编辑、13C/15N过滤的HSQC - NOESY谱的数据来评估配体结合构象，而无需蛋白质NMR共振归属。仅结合配体的1H NMR归属是必需的。通过任何合适的方法（例如计算对接）生成试验性配体结合构象。对于每个试验性结合构象，预测3D 13C编辑、13C/15N过滤的HSQC - NOESY谱，并使用快速、确定性的二分图匹配算法对预测的和观察到的蛋白质 - 配体NOE模式进行匹配和评分。确定得分最高（“成本”最低）的构象。我们的方法可以纳入任何可用的明确约束或蛋白质归属数据，并且基本程序的许多扩展都是可行的。只需要一个样品，并且该方法可应用于缓慢和快速交换的配体。该方法应用于三个测试案例：一个涉及肌肉脂肪酸结合蛋白（mFABP）的复合物和两个涉及白细胞功能相关抗原1（LFA - 1）I结构域的复合物。在不使用实验性蛋白质NMR归属的情况下，该方法以良好的准确性识别出已知的结合构象。添加实验性蛋白质NMR归属可改善结果。我们的“NOE匹配”方法预计将得到广泛应用；即，它似乎不依赖于结合口袋残基的偶然分布。
