Ludwig Institute for Cancer Research, Ltd., Lausanne, Switzerland.
J Comput Chem. 2009 Nov 15;30(14):2305-15. doi: 10.1002/jcc.21244.
In silico screening has become a valuable tool in drug design, but some drug targets represent real challenges for docking algorithms. This is especially true for metalloproteins, whose interactions with ligands are difficult to parametrize. Our docking algorithm, EADock, is based on the CHARMM force field, which assures a physically sound scoring function and a good transferability to a wide range of systems, but also exhibits difficulties in case of some metalloproteins. Here, we consider the therapeutically important case of heme proteins featuring an iron core at the active site. Using a standard docking protocol, where the iron-ligand interaction is underestimated, we obtained a success rate of 28% for a test set of 50 heme-containing complexes with iron-ligand contact. By introducing Morse-like metal binding potentials (MMBP), which are fitted to reproduce density functional theory calculations, we are able to increase the success rate to 62%. The remaining failures are mainly due to specific ligand-water interactions in the X-ray structures. Testing of the MMBP on a second data set of non iron binders (14 cases) demonstrates that they do not introduce a spurious bias towards metal binding, which suggests that they may reliably be used also for cross-docking studies.
计算机筛选已成为药物设计的重要工具,但有些药物靶点对对接算法来说确实是一个挑战。这对于金属蛋白尤其如此,因为它们与配体的相互作用很难参数化。我们的对接算法 EADock 基于 CHARMM 力场,这确保了物理合理的评分函数和对广泛系统的良好可转移性,但在某些金属蛋白的情况下也会遇到困难。在这里,我们考虑了具有活性位点铁核的治疗上重要的血红素蛋白的情况。使用标准对接方案,其中低估了铁配体相互作用,我们对 50 个含铁配体接触的血红素复合物的测试集获得了 28%的成功率。通过引入 Morse 样金属结合势(MMBP),它被拟合以重现密度泛函理论计算,我们能够将成功率提高到 62%。剩余的失败主要是由于 X 射线结构中特定的配体-水相互作用。MMBP 在第二个非铁结合物数据集(14 个案例)上的测试表明,它们不会引入对金属结合的虚假偏差,这表明它们也可可靠地用于交叉对接研究。