Year: 2021
Type: review
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.
Source: Drug Discovery Today
Authors: Joshua Meyers, Benedek Fabian, Nathan Brown
Institution: BenevolentAI (United Kingdom)
Language: English
Subfield: Drug Discovery
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,680
OpenAlex ID: W3165171933