DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learning.

ABSTRACT: Rational drug design often starts from specific scaffolds to which side chains/substituents are added or modified due to the large drug-like chemical space available to search for novel drug-like molecules. With the rapid growth of deep learning in drug discovery, a variety of effective approaches have been developed for de novo drug design. In previous work we proposed a method named DrugEx, which can be applied in polypharmacology based on multi-objective deep reinforcement learning. However, the previous version is trained under fixed objectives and does not allow users to input any prior information (i.e. a desired scaffold). In order to improve the general applicability, we updated DrugEx to design drug molecules based on scaffolds which consist of multiple fragments provided by users

SUBMITTER: Liu X 

PROVIDER: S-EPMC9940339 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature