Chemical programming of kinase inhibitors in a modular chemputer-based system

Area of Science:

• Medicinal Chemistry
• Drug Discovery
• Oncology

Background:

• Manual small molecule synthesis is a bottleneck in drug discovery.
• KRAS-mutant colorectal cancer (K-CRC) presents a significant therapeutic challenge.

Purpose of the Study:

• To apply an automated, modular synthesis platform (Chemputer) for K-CRC drug discovery.
• To develop and optimize lead compounds targeting K-CRC using an integrated digital synthesis and screening system.

Main Methods:

• Automated synthesis of a 4-anilinoquinazoline library via nucleophilic aromatic substitution (SnAr) and Suzuki coupling.
• Phenotypic screening using a transgenic Drosophila model of K-CRC.
• Iterative synthesis and screening cycles enabled by the digital platform.
• Kinase profiling and genetic validation of active compounds.

Main Results:

• Identified hit compound AP2-83, improving survival in the Drosophila model.
• AP2-83 partially inhibits CLK1 and PI3K.
• Optimized compound AP4-43 showed enhanced efficacy in Drosophila and greater potency than regorafenib in CRC organoids.
• AP4-43 acts as a multi-kinase inhibitor targeting CLK1 and NEK4.

Conclusions:

• The digital synthesis platform accelerates lead compound generation and optimization for K-CRC.
• AP4-43 is a promising multi-kinase inhibitor for K-CRC preclinical development.
• Integrated automated synthesis and phenotypic screening is effective for complex drug discovery.