Deep generative models for ligand‐based de novo design applied to multi‐parametric optimization

Multi‐parameter optimization (MPO) is a major challenge in new chemical entity (NCE) drug discovery. Recently, promising results were reported for deep learning generative models applied to de novo molecular design, but, to our knowledge, until now no report was made of the value of this new technol...

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Veröffentlicht in:	Journal of computational chemistry 2022-04, Vol.43 (10), p.692-703
Hauptverfasser:	Perron, Quentin, Mirguet, Olivier, Tajmouati, Hamza, Skiredj, Adam, Rojas, Anne, Gohier, Arnaud, Ducrot, Pierre, Bourguignon, Marie‐Pierre, Sansilvestri‐Morel, Patricia, Do Huu, Nicolas, Gellibert, Françoise, Gaston‐Mathé, Yann
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms artificial intelligence Biological activity Datasets Deep learning Design Design optimization drug discovery Functional groups Lead compounds lead‐optimization Ligands Machine learning multiparameter optimization New technology
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