标题： 配体在蛋白质口袋中的对接 显示英文标题

标题： Group Ligands Docking to Protein Pockets

摘要： 分子对接是计算生物学中的关键任务，近年来引起了机器学习社区的广泛关注。 尽管现有方法取得了成功，但它们通常将每个蛋白质-配体对单独处理。 受生化观察的启发，即结合到同一靶蛋白的配体往往采用相似的构象，我们提出了\textsc{组绑定}，一种新的分子对接框架，该框架同时考虑多个配体对接到蛋白质。 这是通过为配体组引入一个交互层以及为嵌入蛋白质-配体和组-配体对的三角注意力模块来实现的。 通过将我们的方法与基于扩散的对接模型结合，我们在 PDBBind 盲对接基准测试中设定了新的 S 性能，证明了我们提出的分子对接范式的有效性。 显示英文摘要

摘要： Molecular docking is a key task in computational biology that has attracted increasing interest from the machine learning community. While existing methods have achieved success, they generally treat each protein-ligand pair in isolation. Inspired by the biochemical observation that ligands binding to the same target protein tend to adopt similar poses, we propose \textsc{GroupBind}, a novel molecular docking framework that simultaneously considers multiple ligands docking to a protein. This is achieved by introducing an interaction layer for the group of ligands and a triangle attention module for embedding protein-ligand and group-ligand pairs. By integrating our approach with diffusion-based docking model, we set a new S performance on the PDBBind blind docking benchmark, demonstrating the effectiveness of our proposed molecular docking paradigm.