Researchers from Insilico Medicine (“Insilico”), a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, have discovered a new class of Pol? inhibitors featuring central scaffolding rings, designed using Chemistry42, the Company’s proprietary generative AI platform. According to the findings, the AI-enabled molecules exhibited significant enzymatic and cellular potency and promising druglike properties, pointing to a novel strategy for targeting Pol?. The research was published in Bioorganic & Medicinal Chemistry, an Elsevier peer-reviewed journal focusing on molecular chemistry and biology.
Aiming for a novel and potent Pol? inhibitor with new cores, the Insilico R&D team implemented both ligand-based drug design (LBDD) and structure-based drug design (SBDD) strategies. Based on novel central scaffold rings innovated with the help of Chemistry42, a promising lead compound was identified, and further optimization for improved potency and other druglike properties yielded 3-hydroxymethyl-azetidine derivatives as a novel class of Pol? inhibitors.
In consequent validation, a novel compound exhibited robust cellular potency in DNA repair-compromised cells, as well as favorable ADME profiles and pharmacokinetic properties in vivo. This orally bioavailable molecule shows potential as a possible treatment approach for solid cancers with BRCA1/2 mutations, and the findings demonstrate the potential of using AI in medicinal chemistry for precise molecular modifications.
https://www.sciencedirect.com/science/article/abs/pii/S0968089624000762?via%3Dihub
