Multimodal Alignment and Preference Optimization for Zero-Shot Conditional RNA Generation
Researchers have developed Moirain, a new suite of models for generating RNA sequences that can interact with specific proteins. This approach uses multimodal supervised fine-tuning and Direct Preference Optimization, building on large-scale pretraining of RNA corpora. Moirain aims to improve the success rate of functional RNA design by conditioning generation on protein structural and sequential features, and refining the model with synthetic interaction data to enhance binding affinities. AI
IMPACT Introduces a novel AI framework for designing functional RNA molecules, potentially accelerating drug discovery and synthetic biology.