Deep-Learning-Driven Discovery of SN3–1, a Potent NLRP3 Inhibitor with Therapeutic Potential for Inflammatory Diseases

The
NLRP3 inflammasome plays a central role in the pathogenesis
of various intractable human diseases, making it an urgent target
for therapeutic intervention. Here, we report the development of SN3–1,
a novel orally potent NLRP3 inhibitor, designed through a lead compound
strategy centered on deep-learning-based molecular generative models.
Our strategy enables rapid fragment enumeration and takes into account
the synthetic accessibility of the compounds, thereby significantly
enhancing the optimization of lead compounds and facilitating the
discovery of potent inhibitors. X-ray crystallography provided insights
into the SN3–1 inhibitory mechanism. SN3–1 has shown
a favorable safety profile in both acute and chronic toxicity assessments
and exhibits robust pharmacokinetic properties. Furthermore, SN3–1
demonstrated significant therapeutic efficacy in various disease models
characterized by NLRP3 activation. This study introduces a potent
candidate for developing NLRP3 inhibitors and significantly expands
the repertoire of tools available for the discovery of novel inhibitors.