Enabling target-aware molecule generation to follow multi objectives with Pareto MCTS.

ABSTRACT: Target-aware drug discovery has greatly accelerated the drug discovery process to design small-molecule ligands with high binding affinity to disease-related protein targets. Conditioned on targeted proteins, previous works utilize various kinds of deep generative models and have shown great potential in generating molecules with strong protein-ligand binding interactions. However, beyond binding affinity, effective drug molecules must manifest other essential properties such as high drug-likeness, which are not explicitly addressed by current target-aware generative methods. In this article, aiming to bridge the gap of multi-objective target-aware molecule generation in the field of deep learning-based drug discovery, we propose ParetoDrug, a Pareto Monte Carlo Tree Search (MCTS) generati

SUBMITTER: Yang Y 

PROVIDER: S-EPMC11368924 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature