ReACT-Drug: Reaction-Template Guided Reinforcement Learning for de novo Drug Design

This article introduces ReACT-Drug, a novel approach to de novo drug design using reinforcement learning guided by reaction templates. The use of reaction templates likely improves the efficiency and accuracy of the drug design process by focusing the search space on chemically plausible reactions. The application of reinforcement learning suggests an iterative optimization process, potentially leading to the discovery of novel drug candidates.

• •ReACT-Drug utilizes reinforcement learning for de novo drug design.
• •The approach is guided by reaction templates.
• •This method aims to improve efficiency and accuracy in drug discovery.