TamGen: drug design with target-aware molecule generation through a chemical language model.

ABSTRACT: Generative drug design facilitates the creation of compounds effective against pathogenic target proteins. This opens up the potential to discover novel compounds within the vast chemical space and fosters the development of innovative therapeutic strategies. However, the practicality of generated molecules is often limited, as many designs focus on a narrow set of drug-related properties, failing to improve the success rate of subsequent drug discovery process. To overcome these challenges, we develop TamGen, a method that employs a GPT-like chemical language model and enables target-aware molecule generation and compound refinement. We demonstrate that the compounds generated by TamGen have improved molecular quality and viability. Additionally, we have integrated TamGen into a drug disc

SUBMITTER: Wu K 

PROVIDER: S-EPMC11522292 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature