The Boolean logic tree of molecular self-assembly system based on cobalt oxyhydroxide nanoflakes for three-state logic computation, sensing and imaging of pyrophosphate in living cells and in vivo
Literature Information
Xin Xing Zhang, Qiu Yan Zhu, Jiao Yang Lu, Fu Rui Zhang, Wei Tao Huang, Xue Zhi Ding, Li Qiu Xia
Sensing of pyrophosphate (PPi) is helpful to better understand many life processes and diagnose various early-stage diseases. However, many traditional reported methods based on artificial receptors for sensing of PPi exhibit some disadvantages including difficulties in designing appropriate binding sites and complicated multi-step assembly/functionalization. Thus, it is significantly important and a big challenge to know how to use a simple molecular self-assembly or an interaction system to solve the above-mentioned limits to achieve the quantitative analysis of specific substances in the system. Based on the natural connection and similarity (such as stimulus responsiveness) between sensing and logic computing, in this study, the Boolean logic tree of molecular self-assembly system based on the cobalt oxyhydroxide (CoOOH) nanoplatform is constructed and applied to organize and connect “plug and play” molecular events (fluorescent dye, acridine orange and anion, PPi). By using molecules as inputs and the corresponding fluorescence signal as the output, the CoOOH-based molecular self-assembly system can be programmed for three-input fluorescent Boolean logic computation, fluorescent three-state logic computation, detection of PPi (linear range from 50 to 6400 nM with a detection limit of 20 nM) and even for imaging in living cancer cells and in vivo (in systems such as Zebrafish and Carassius auratus). Our approach adds a new dimension for expanding molecular logic computing and sensing systems, which will not only provide more opportunities for developing novel logic computing paradigms, but also be helpful in promoting the development and applications of intelligent molecular computing and sensing systems.
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