Leiden Institute of Chemistry, Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands.
J Chem Inf Model. 2023 Dec 25;63(24):7816-7825. doi: 10.1021/acs.jcim.3c01582. Epub 2023 Dec 4.
Despite the proven potential of metal complexes as therapeutics, the lack of computational tools available for the high-throughput screening of their interactions with proteins is a limiting factor toward clinical developments. To address this challenge, we introduce MetalDock, an easy-to-use, open access docking software for docking metal complexes to proteins. Our tool integrates the AutoDock docking engine with three well-known quantum software packages to automate the docking of metal-organic complexes to proteins. We used a Monte Carlo sampling scheme to obtain the missing Lennard-Jones parameters for 12 metal atom types and demonstrated that these parameters generalize exceptionally well. Our results show that the poses obtained by MetalDock are highly accurate, as they predict the binding geometries experimentally determined by crystal structures with high spatial reproducibility. Three different case studies are presented that demonstrate the versatility of MetalDock for the docking of diverse metal-organic compounds to different biomacromolecules, including nucleic acids.
尽管金属配合物作为治疗药物具有明显的潜力，但缺乏可用于高通量筛选其与蛋白质相互作用的计算工具，这是阻碍其临床开发的一个因素。为了解决这一挑战，我们引入了 MetalDock，这是一款易于使用的、开放获取的对接软件，用于对接金属配合物与蛋白质。我们的工具将 AutoDock 对接引擎与三个著名的量子软件包集成在一起，实现了金属有机配合物与蛋白质的自动对接。我们使用蒙特卡罗采样方案为 12 种金属原子类型获取缺失的 Lennard-Jones 参数，并证明这些参数具有非常好的通用性。我们的结果表明，MetalDock 获得的构象非常准确，因为它们能够以高空间重现性预测晶体结构实验测定的结合几何形状。我们展示了三个不同的案例研究，证明了 MetalDock 在对接不同的金属有机化合物与不同的生物大分子（包括核酸）方面的多功能性。
