Zhe Nie, Michael Trzoss, Andrew T. Placzek, Lynnie Trzoss, Goran Krilov, Shulu Feng, Morgan Lawrenz, Min Ye, Netonia Marshall, Karen H. Dingley, Robert Pelletier, Weidong G. Lai, Jeffrey A. Bell, Haifeng Tang, Paul Devine, Zhijian Liu, Peter J. Skrdla, Roman Shimanovich, Matt Liu, Renchao Wang, Xiaoming Xu, Sathesh Bhat, Pieter H. Bos, Robert Abel, Karen Akinsanya, Wu Yin
Abstract MALT1 is a key component of the CARD11-BCL10-MALT1 (CBM) complex downstream from BTK on the B-cell receptor signaling pathway. It is a key mediator of NF-κB signaling and considered a potential therapeutic target for several subtypes of non-Hodgkin’s B-cell lymphomas. By applying advanced physics-based modeling techniques, including combining free energy calculations with machine learning methods and a chemistry-aware compound enumeration workflow, extensive sets of de novo design ideas were explored to quickly identify a novel hit series. Multiparameter optimization allowed efficient prioritization of molecules with good potency and drug-like properties during lead optimization, which led to the discovery of a highly potent MALT1 inhibitor, SGR-1505, with a well-balanced property profile. It demonstrated strong antitumor activity alone and in combination with BTK inhibitor in multiple in vivo B-cell lymphoma xenograft models and progressed to a phase 1 clinical trial in patients with mature B-cell neoplasms.