Atomwise’s Post

Promising news for cancer research! A team from the University of Pavia, Italy, leveraged AtomNet #AI to design small molecules targeting Voltage-dependent Anion-selective Channel 1 (VDAC1), a protein implicated in various cancers. Their approach focused on immobilizing a flexible helix within VDAC1, thereby modifying a metabolite binding site and a putative protein-protein interaction (PPI) implicated in tumor cell proliferation. These VDAC1 molecular glues demonstrated dose-dependent efficacy in reducing cancer cell viability while exhibiting minimal impact on healthy cells and organoids. The research lays a foundation for future development of these molecules as potential cancer therapeutics. Read more here: https://lnkd.in/e3wp5kHd

The verdict is in! Our proprietary AtomNet #AI platform is a viable alternative to high-throughput screening for discovering structurally novel chemical matter, regardless of the target: https://lnkd.in/ebPpWhnH In the largest, most comprehensive virtual high-throughput screening campaign of its kind, we applied AtomNet to 318 targets covering a wide range of classes. AtomNet found hits for 235 targets, averaging over seven structurally distinct bioactive compounds per target. Even more impressively, most of the targets assessed lacked any target-specific training data, with hits representing first-in-class binders to the target. Check out our publication in Nature Scientific Reports for more details: https://lnkd.in/eFcNAC3S We believe that AtomNet's ability to find novel chemical matter even for data-poor targets is a significant achievement in the field of AI #DrugDiscovery. We are grateful to our 600 talented collaborators who contributed to this effort!

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