From small molecules to oligonucleotides: artificial intelligence for RNA-targeted drug discovery

Abstract

Artificial intelligence (AI) has advanced rapidly in recent years, offering transformative opportunities across chemistry and the biological sciences. Yet effectively integrating these tools into everyday research remains a key challenge. This mini review summarizes recent advances in applying AI to RNA-targeted drug discovery, encompassing both small-molecule approaches and oligonucleotide therapeutics. It examines how AI-driven RNA structure prediction, target-site discovery, and interaction prediction underpin both modalities. Current limitations and future opportunities are also discussed, with particular emphasis on improving the reliability, automation, and translational utility of AI-enabled therapeutic design.