Explaining and avoiding failure modes in goal-directed generation of small molecules

Explaining and avoiding failure modes in goal-directed generation of small molecules

Abstract Despite growing interest and success in automated in-silico molecular design, questions remain regarding the ability of goal-directed generation algorithms to perform unbiased exploration of novel chemical spaces. A specific phenomenon has recently been highlighted: goal-directed generation...

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Bibliographic Details
Main Authors: Maxime Langevin, Rodolphe Vuilleumier, Marc Bianciotto
Format: Article
Language:English
Published: BMC 2022-04-01
Series:Journal of Cheminformatics
Subjects:
De novo design
Generative models
Goal-directed generation
Recurrent neural network
Reinforcement learning
Failure modes
Online Access:https://doi.org/10.1186/s13321-022-00601-y

Internet

https://doi.org/10.1186/s13321-022-00601-y

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