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Matcha model makes drug candidate screening more than 30 times faster

  • April 7, 2026 at 1:20 PM
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Matcha model makes drug candidate screening more than 30 times faster
Ligand Pro, founded by Skoltech professors and a Skoltech Ph.D. student, has presented Matcha, an AI-powered molecular docking model that performs virtual drug screening 30 times faster than the large co-folding models of the AlphaFold class developed by Nobel laureates, while surpassing them in both accuracy and physical correctness of the results. Matcha opens up new possibilities for virtual screening and early-stage drug development.

Originally published at Phys.org

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