Article
Author: Krilov, Goran ; Lai, W. George ; Xu, Xiaoming ; Feng, Shulu ; Tang, Haifeng ; Liu, Zhijian ; Nie, Zhe ; Bell, Jeffrey A. ; Dingley, Karen H. ; Placzek, Andrew T. ; Yin, Wu ; Bos, Pieter H. ; Abel, Robert ; Devine, Paul ; Liu, Matt ; Wang, Renchao ; Pelletier, Robert D. ; Skrdla, Peter ; Bhat, Sathesh ; Trzoss, Lynnie ; Marshall, Netonia ; Shimanovich, Roman ; Trzoss, Michael ; Lawrenz, Morgan ; Ye, Min ; Akinsanya, Karen
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.