2026-10-06T07:27:23Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34037489 2026-10-01T01:06:06Z category_1 category_4 category_14 category_21 category_734 category_931 portal_63 item_type_6 month_year_10_2026

De Novo Design of Hydrogen-Bonding Networks for Deterministic Bio-Nano Recognition Li Zhu (67404) Yinong Li (5112956) Yannan Feng (7347269) Junran Luo (25147298) Jian Li (41607) Shishan Tian (25147301) Zhiwei Lin (1423945) Biophysics Biochemistry Molecular Biology Biotechnology Biological Sciences not elsewhere classified Information Systems not elsewhere classified wall carbon nanotube universal tuning knob three rare quasi structural programmability enables nano interfaces remains helical periodicity (< 21 distinct (< 150 designed sequences tailored molecular discrimination error sequence screening rational design paradigm de novo </ interfacial dna pitch >) swcnt species molecular recognition empirical screening >) serves work transitions two decades swcnt sensors success rate strategy achieved purity isolation mediating chirality mediated single fundamental challenge framework enabled extraordinary 91 experimentally evaluated electrochemical resilience driven compiler design framework curvature bio bonding networks bonding network 2 ), 1 ) Achieving deterministic control over molecular recognition at high-curvature bio-nano interfaces remains a fundamental challenge. 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. Mechanistically, the helical periodicity (<i>N</i>) serves as a universal tuning knob to coordinately modulate nanotube diameter and interfacial DNA pitch. This structural programmability enables the “bespoke” engineering of DNA-SWCNT sensors with tailored molecular discrimination and electrochemical resilience. This work transitions the field from labor-intensive, trial-and-error sequence screening to a deterministic, rational design paradigm. 2026-09-30T00:00:00Z Text Journal contribution 10.1021/jacs.6c11726.s001 https://figshare.com/articles/journal_contribution/De_Novo_Design_of_Hydrogen-Bonding_Networks_for_Deterministic_Bio-Nano_Recognition/34037489 CC BY-NC 4.0