Subpocket Similarity-Based Hit Identification for Challenging Targets: Application to the WDR Domain of LRRK2

• DOI: 10.1021/acs.jcim.4c00601
• Publication Date: 2024-06-25T10:44:09Z
• Authors: Merveille Eguida; Guillaume Bret; François Sindt; Fengling Li; Irene Chau; Suzanne Ackloo; Cheryl Arrowsmith; Albina Bolotokova; Pegah Ghiabi; Elisa Gibson; Levon Halabelian; Scott Houliston; Rachel J. Harding; Ashley Hutchinson; Peter Loppnau; Sumera Perveen; Almagul Seitova; Hong Zeng; Matthieu Schapira; Didier Rognan
• Keywords: 0301 basic medicine; 03 medical and health sciences

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.