We describe a new template-based method for docking flexible ligands such as macrocycles to proteins. It combines Monte-Carlo energy minimization on the manifold, a fast manifold search method, with BRIKARD for complex flexible ligand searching, and with the MELD accelerator of Replica-Exchange Molecular Dynamics simulations for atomistic degrees of freedom. Here we test the method in the Drug Design Data Resource blind Grand Challenge competition. This method was among the best performers in the competition, giving sub-angstrom prediction quality for the majority of the targets.

中文翻译：

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基于模板的大周期对接的采样和优化协议：2018 D3R Grand Challenge 4。

我们描述了一种基于模板的新方法，用于将诸如大环等柔性配体对接至蛋白质。它结合了流形上的蒙特卡洛能量最小化，快速流形搜索方法，用于复杂柔性配体搜索的BRIKARD以及用于原子自由度的仿制交换分子动力学模拟的MELD加速器。在这里，我们在“药品设计数据资源”盲目的大挑战赛中测试了该方法。这种方法是竞争中表现最好的方法之一，它为大多数目标提供了亚埃的预测质量。