RLSynC: Offline-Online Reinforcement Learning for Synthon Completion.

ABSTRACT: Retrosynthesis is the process of determining the set of reactant molecules that can react to form a desired product. Semitemplate-based retrosynthesis methods, which imitate the reverse logic of synthesis reactions, first predict the reaction centers in the products and then complete the resulting synthons back into reactants. We develop a new offline-online reinforcement learning method RLSynC for synthon completion in semitemplate-based methods. RLSynC assigns one agent to each synthon, all of which complete the synthons by conducting actions step by step in a synchronized fashion. RLSynC learns the policy from both offline training episodes and online interactions, which allows RLSynC to explore new reaction spaces. RLSynC uses a standalone forward synthesis model to evaluate the likeli

SUBMITTER: Baker FN 

PROVIDER: S-EPMC11388466 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature