De novo molecular design and generative models.

Journal: Drug discovery today
Published Date:

Abstract

Molecular design strategies are integral to therapeutic progress in drug discovery. Computational approaches for de novo molecular design have been developed over the past three decades and, recently, thanks in part to advances in machine learning (ML) and artificial intelligence (AI), the drug discovery field has gained practical experience. Here, we review these learnings and present de novo approaches according to the coarseness of their molecular representation: that is, whether molecular design is modeled on an atom-based, fragment-based, or reaction-based paradigm. Furthermore, we emphasize the value of strong benchmarks, describe the main challenges to using these methods in practice, and provide a viewpoint on further opportunities for exploration and challenges to be tackled in the upcoming years.

Authors

  • Joshua Meyers
    BenevolentAI, London W1T 5HD, U.K.
  • Benedek Fabian
    BenevolentAI, 4-8 Maple Street, London W1T 5HD, UK.
  • Nathan Brown
    BenevolentAI, 40 Churchway, London, NW1 1LW, UK.