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Paper on AI-Driven Discovery of Novel Chemical Scaffolds Published in ChemMedChem
2026.07.31
Integrative Molecular Scaffold Generation of PI3K/mTOR Inhibitors Using DeepSARM and Ligand-Based Virtual Screening Approaches
Publication
Published Date: 08 July 2026
Research results led by Chordia Therapeutics have been published in ChemMedChem.
Paper Summary
This study evaluated the effectiveness of AI-driven drug discovery technologies by using the PI3K/mTOR inhibitor samotolisib as a starting point. Researchers combined the AI-based molecular design platform DeepSARM with virtual screening to generate novel compounds. As a result, they successfully designed and synthesized compounds with novel chemical scaffolds that exhibit PI3Kα inhibitory activity, distinct from those of existing drugs. Furthermore, analysis using the AI-powered molecular modeling technology Boltz-2 suggested a rational binding mode between the compounds and the target protein. These findings demonstrate the potential of AI and computational science to efficiently generate novel chemical scaffolds for drug discovery.
Axcelead contributed to this research by evaluating the compounds through enzyme inhibition assays.
Axcelead DDP Solution
Axcelead has extensive expertise and experience in developing a wide range of assay systems, including enzyme inhibition assays and evaluating compounds, with a proven track record of supporting the research activities of numerous customers. If you are considering compound evaluation services for your drug discovery program, we invite you to contact us to learn how we can support your research.
Mitsuyo Kondo, Discovery Technologies Business Unit
After graduating from the Faculty of Agriculture at Nagoya University, she worked at Takeda Pharmaceutical Company Limited before joining Axcelead Drug Discovery Partners, Inc. She is responsible for developing cell-free assay systems, managing screening campaigns, and evaluating compounds.