Combining Artificial Intelligence and Human Expertise in Pursuit of Novel PolQ Inhibitors

Sygnature Discovery, in collaboration with Iktos, presents a poster outlining the use of AI drug discovery to design and optimize a novel scaffold of PolQ inhibitors. Through iterative generative design, medicinal chemistry refinement and early ADME assessment, the project highlights how AI and expert-driven design can work together to accelerate discovery of precision oncology therapies.

Study Highlights:

• Generative AI for scaffold identification
• Potency improvement through medicinal chemistry
• Favourable early ADME profiles
• Precision oncology approach via DDR targeting

Advancing PolQ Inhibitor Design Through AI Drug Discovery

This study demonstrates how PolQ inhibitors can be designed and optimized rapidly using AI drug discovery methods combined with expert medicinal chemistry. The resulting compounds show promise for further preclinical profiling in DNA damage response-driven oncology strategies.

Explore out AI-Integrated Discovery Chemistry Expertise

Sygnature Discovery supports AI-guided small molecule discovery through integrated medicinal chemistry, targeted protein degradation and DDR biology, and ADME profiling. Whether using generative AI tools, structural modelling or traditional screening, our teams accelerate hit-to-lead optimization and compound profiling.