GexMolGen: cross-modal generation of hit-like molecules via large language model encoding of gene expression signatures.

ABSTRACT: Designing de novo molecules with specific biological activity is an essential task since it holds the potential to bypass the exploration of target genes, which is an initial step in the modern drug discovery paradigm. However, traditional methods mainly screen molecules by comparing the desired molecular effects within the documented experimental results. The data set limits this process, and it is hard to conduct direct cross-modal comparisons. Therefore, we propose a solution based on cross-modal generation called GexMolGen (Gene Expression-based Molecule Generator), which generates hit-like molecules using gene expression signatures alone. These signatures are calculated by inputting control and desired gene expression states. Our model GexMolGen adopts a "first-align-then-generate" st

SUBMITTER: Cheng J 

PROVIDER: S-EPMC11514063 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature