Accelerated Discovery of Carbamate Cbl‑b Inhibitors Using Generative AI Models and Structure-Based Drug Design

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.