Critical Assessment of Generative Models for de Novo Molecular Structure Generation

抄録

Deep generative models can virtually generate chemical structures with desired properties. These models are widely used in de-novo molecular design projects, and are becoming an alternative to conventional approaches to chemical structure generation. Although the usefulness of the generative models has already been proven in retrospective validations: using an already known data set, deployment of the generative models in applications has not been frequently reported. Herein, several research articles are surveyed where deep generative models are employed in de novo molecular design projects to clarify the usage of the generative models for successful de novo design.