Aim of this project is the development of a computational pipeline to design biohybrid materials consisting of protein binders for predefined sequences in nucleic acids (NA), enabling the development of tools for cargo encapsulation and delivery as well as diagnostic tests including viral infections. Previously we have developed a pipeline for target peptide sensing by adjusting the binding pockets of natural membrane receptor systems comprised of proteins whose dimerization and signalling relies on extracellular peptide binding. The doctoral candidate will combine state-of-the-art physics- and artificial intelligence-based prediction and design methods to develop an analogous pipeline for specific targeting of DNA and RNA secondary structure motifs, using as inspiration natural NA-binding proteins. Through rounds of design-build-test-learn, we will establish a library of building blocks for NA binders in complex environments.