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首页> 外文期刊>Journal of Medicinal Chemistry >SDOCKER: A Method Utilizing Existing X-ray Structures To Improve Docking Accuracy
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SDOCKER: A Method Utilizing Existing X-ray Structures To Improve Docking Accuracy

机译：SDOCKER：一种利用现有X射线结构提高对接精度的方法

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This paper introduces a new strategy for structure-based drug design that combines high-quality docking with data from existing ligand-protein cocrystal X-ray structures. The main goal of SDOCKER, a new algorithm that implements this strategy, is docking accuracy improvement. In this new paradigm, simulated annealing molecular dynamics is used for conformational sampling and optimization and an additional similarity force is applied on the basis of the positions of ligands from X-ray data that focus the sampling on relevant regions of the active site. Because the structural information from both the ligand and protein active site is included, this approach is more effective in finding the optimal conformation for a ligand-protein complex than the classical docking or similarity overlays. Interestingly, it was found that a 3D similarity-only approach gives comparable docking accuracy to the regular force field approach used in classical docking, given the final structures are minimized in the presence of the protein. The combination of both, as implemented in SDOCKER, is shown here to be more accurate. A significant improvement in docking accuracy has been observed for three different test systems. Specifically an improvement of 10%, 17.5%, and 10% is seen for 37 HIV-1 protease, 32 thrombin, and 23 CDK2 ligands, respectively, compared to docking using the force field alone. In addition, SDOCKER's accuracy performance dependence on the similarity template is discussed. The strategy of utilizing existing ligand X-ray information should prove effective in light of the multitude of structures available from structural genomics approaches.
机译：本文介绍了一种基于结构的药物设计新策略，该策略将高质量的对接与现有配体-蛋白质共晶体X射线结构的数据相结合。实现此策略的新算法SDOCKER的主要目标是提高对接精度。在这种新范式中，模拟退火分子动力学用于构象采样和优化，并且基于来自X射线数据的配体位置（将采样集中在活性部位的相关区域上）施加了额外的相似力。因为包括了来自配体和蛋白质活性位点的结构信息，所以该方法比经典的对接或相似性覆盖图更有效地为配体-蛋白质复合物寻找最佳构象。有趣的是，发现3D仅相似性方法可提供与经典对接中使用的常规力场方法相当的对接精度，前提是在存在蛋白质的情况下将最终结构最小化。如SDOCKER中所实现的，两者的组合在此处显示为更准确。对于三种不同的测试系统，已观察到对接精度的显着提高。与仅使用力场对接相比，分别对37个HIV-1蛋白酶，32个凝血酶和23个CDK2配体分别提高了10％，17.5％和10％。此外，还讨论了SDOCKER对相似性模板的准确性性能依赖性。鉴于结构基因组学方法可利用的许多结构，利用现有配体X射线信息的策略应被证明是有效的。

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