Focused Library Generator: case of Mdmx inhibitors

We present a Focused Library Generator that is able to create from scratch new molecules with desired properties. After training the Generator on the ChEMBL database, transfer learning was used to switch the generator to producing new Mdmx inhibitors that are a promising class of anticancer drugs. Lilly medicinal chemistry filters, molecular docking, and a QSAR IC₅₀ model were used to refine the output of the Generator. Pharmacophore screening and molecular dynamics (MD) simulations were then used to further select putative ligands. Finally, we identified five promising hits with equivalent or even better predicted binding free energies and IC₅₀ values than known Mdmx inhibitors. The source code of the project is available on https://github.com/bigchem/online-chem.