PRAADA-designer
Abstract
This work establishes a generalizable framework for designing programmable RNA sensors that enable transcript- and cell-type-specific selection, editing, and perturbation at scale. We integrate ADAR-based RNA editing with pooled sensor libraries, high-throughput sequencing, and predictive modeling to develop a platform capable of rationally engineering sensors for virtually any cell type. Our PRAADA computational workflow will use LLMs to design editable ADAR protein sites and test its design across any mammalian systems for protein convergence.