Sc2Mol: a scaffold-based two-step molecule generator with variational autoencoder and transformer.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Finding molecules with desired pharmaceutical properties is crucial in drug discovery. Generative models can be an efficient tool to find desired molecules through the distribution learned by the model to approximate given training data. Existing generative models (i) do not consider backbone structures (scaffolds), resulting in inefficiency or (ii) need prior patterns for scaffolds, causing bias. Scaffolds are reasonable to use, and it is imperative to design a generative model without any prior scaffold patterns.

Authors

  • Zhirui Liao
    School of Computer Science, Fudan University, Shanghai 200433, China.
  • Lei Xie
    Ph.D. Program in Computer Science, The City University of New York, New York, NY, United States.
  • Hiroshi Mamitsuka
    Bioinformatics Center, Institute of Chemical Research, Kyoto University, Uji, Kyoto, 611 - 0011, Japan.
  • Shanfeng Zhu