化学
药物发现
生物信息学
效应器
药品
立体化学
计算生物学
药理学
生物化学
基因
生物
作者
Taylor R. Quinn,Kathryn A. Giblin,Clare Thomson,Jeffrey A. Boerth,Gayathri Bommakanti,Erin Braybrooke,Christina Chan,Alex J. Chinn,Erin Code,Caifeng Cui,Yukai Fan,Neil P. Grimster,Keishi Kohara,Michelle L. Lamb,Lina Ma,Adelphe M. Mfuh,Graeme R. Robb,Kevin J. Robbins,Marianne Schimpl,Haoran Tang
标识
DOI:10.1021/acs.jmedchem.4c01034
摘要
Casitas B-lymphoma proto-oncogene-b (Cbl-b) is a RING finger E3 ligase that has an important role in effector T cell function, acting as a negative regulator of T cell, natural killer (NK) cell, and B cell activation. A discovery effort toward Cbl-b inhibitors was pursued in which a generative AI design engine, REINVENT, was combined with a medicinal chemistry structure-based design to discover novel inhibitors of Cbl-b. Key to the success of this effort was the evolution of the "Design" phase of the Design-Make-Test-Analyze cycle to involve iterative rounds of an in silico structure-based drug design, strongly guided by physics-based affinity prediction and machine learning DMPK predictive models, prior to selection for synthesis. This led to the accelerated discovery of a potent series of carbamate Cbl-b inhibitors.
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