BACKGROUND Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. RESULTS Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. CONCLUSIONS Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking.

中文翻译：

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当大型配体与蛋白质对接时，使用并行化的增量对接可以解决构象采样问题。

背景技术将大的配体，特别是肽对接至蛋白质受体，仍然被认为是计算结构生物学中的挑战。除了对分子对接工具产生的蛋白质-配体复合物的结合模式进行精确评分的问题外，由于其潜在的组合复杂性，通常也认为对大配体的构象取样是一个挑战。在这项研究中，我们评估了对接大型配体时，使用并行和增量范式对构象采样的准确性和性能的影响。我们使用五个包含配体的蛋白质-配体复合物的数据集，这些数据在以前的类似研究中无法通过经典的蛋白质-配体对接工具精确对接。结果我们的计算评估表明，仅通过长时间运行蛋白配体对接工具（例如Vina）来增加构象采样的数量几乎是没有好处的。取而代之的是，以一种简单的并行化对接协议并行运行此对接工具的多个短实例，并将其结果分组在一起，将更加有效和有利。我们的并行化增量式对接工具DINC实现了更高的准确性和效率，显示了其增量范式的其他优势。使用DINC，我们可以准确地复制我们考虑的绝大多数蛋白质-配体复合物。结论我们的研究表明，即使试图将大型配体与蛋白质对接，配体的构象取样也不应再成为问题，因为使用现有工具的简单对接协议可以解决该问题。因此，评分目前应被视为分子对接中最大的未满足挑战。