Abstract：
We herewith applied a priori a generic hit identification method (POEM) for difficult targets of known three-dimensional structure, relying on the simple knowledge of physicochemical and topological properties of a user-selected cavity. Searching for local similarity to a set of fragment-bound protein microenvironments of known structure, a point cloud registration algorithm is first applied to align known subpockets to the target cavity. The resulting alignment then permits us to directly pose the corresponding seed fragments in a target cavity space not typically amenable to classical docking approaches. Last, linking potentially connectable atoms by a deep generative linker enables full ligand enumeration. When applied to the WD40 repeat (WDR) central cavity of leucine-rich repeat kinase 2 (LRRK2), an unprecedented binding site, POEM was able to quickly propose 94 potential hits, five of which were subsequently confirmed to bind in vitro to LRRK2-WDR.
摘要：
我们在此对已知三维结构的困难目标应用了先验的通用命中识别方法（POEM），依靠用户选择的腔体的物理化学和拓扑特性的简单知识。寻找与一组已知结构的片段结合的蛋白质微环境的局部相似性，首先应用点云配准算法以将已知子袋对准到目标腔。然后，所产生的对准允许我们将相应的种子片段直接放置在通常不适合经典对接方法的目标腔空间中。最后,通过深层生成接头连接潜在可连接的原子，可以进行完整的配体计数。当应用于富亮氨酸重复激酶2（LRRK2）的WD40重复（WDR）中央腔时，一个前所未有的结合位点，POEM能够迅速提出94次潜在命中，其中5种随后被证实在体外与LRRK2-WDR结合。
