PuSH - Publication Server of Helmholtz Zentrum München

Xia, Z. ; Karpov, P. ; Popowicz, G.M. ; Tetko, I.V.

Focused library generator: Case of Mdmx inhibitors.

J. Comput.-Aided Mol. Des. 34, 769–782 (2020)
Postprint DOI PMC
Open Access Green
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.
Altmetric
Additional Metrics?
[➜Log in]
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Lstm ; Mdmx Inhibitors ; Molecular Dynamics ; Pharmacophore ; Structure Generation ; Transfer Learning; P53; Database; Protein; Identification; Discovery; Optimization; Methodology; Molecules; Chemistry; Accuracy
ISSN (print) / ISBN 0920-654X
e-ISSN 1573-4951
Journal Journal of Computer-Aided Molecular Design
Quellenangaben Volume: 34, Issue: , Pages: 769–782 Article Number: , Supplement: ,
Publisher Springer
Publishing Place Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Structural Biology (STB)