Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, Mail TPC-28, La Jolla, California 92037, USA.
J Chem Inf Model. 2010 Jan;50(1):186-93. doi: 10.1021/ci9003943.
The use of multiple X-ray protein structures has been reported to be an efficient alternative for the representation of the binding pocket flexibility needed for accurate small molecules docking. However, the docking performance of the individual single conformations varies widely, and adding certain conformations to an ensemble is even counterproductive. Here we used a very large and diverse benchmark of 1068 X-ray protein conformations of 99 therapeutically relevant proteins, first, to compare the performance of the ensemble and single-conformation docking and, second, to find the properties of the best-performing conformers that can be used to select a smaller set of conformers for ensemble docking. The conformer selection has been validated through retrospective virtual screening experiments aimed at separating known ligand binders from decoys. We found that the conformers cocrystallized with the largest ligands displayed high selectivity for binders, and when combined in ensembles they consistently provided better results than randomly chosen protein conformations. The use of ensembles encompassing between 3 and 5 experimental conformations consistently improved the docking accuracy and binders vs decoys separation.
使用多个 X 射线蛋白质结构已被报道为一种有效的替代方法，可用于表示准确小分子对接所需的结合口袋灵活性。然而，各个单构象的对接性能差异很大，并且向集合中添加某些构象甚至适得其反。在这里，我们使用了一个非常大且多样化的 99 种治疗相关蛋白质的 1068 个 X 射线蛋白质构象基准，首先比较了集合和单构象对接的性能，其次找到了性能最佳构象的特性，这些特性可用于为集合对接选择更小的构象集。构象选择已通过旨在将已知配体结合物与诱饵分离的回顾性虚拟筛选实验进行了验证。我们发现，与最大配体共结晶的构象对结合物具有高选择性，并且当它们组合在集合中时，它们始终提供比随机选择的蛋白质构象更好的结果。使用包含 3 到 5 个实验构象的集合可以一致地提高对接准确性和结合物与诱饵的分离。
