De Novo Design of Hydrogen-Bonding Networks for Deterministic Bio-Nano Recognition

For two decades, DNA-mediated single-wall carbon nanotube (SWCNT) sorting has relied on empirical screening, leaving the underlying recognition code largely undeciphered. Here, we report a <i>de novo</i> design framework that rationally programs DNA sequences via a generalized hydrogen-bonding network (HBN) model.

Navigating the vast sequence space via an automated HBN-driven compiler, we experimentally evaluated a library of 150 designed sequences. This strategy achieved an extraordinary 91.3% success rate in mediating chirality-specific sorting, facilitating the high-purity isolation of 21 distinct (<i>n, m</i>) SWCNT species. Notably, this framework enabled the capture of three rare quasi-metallic nanotubes(8,2), (9,3), and (10,1)which were previously inaccessible via conventional screening.