A label-free visual platform for self-correcting logic gate construction and sensitive biosensing based on enzyme-mimetic coordination polymer nanoparticles

In molecular logic gates, the occurrence of erroneous procedures is a frequently encountered and critical problem in data transmission, and thus it is highly desirable to develop novel logic systems with self-correction abilities. Herein, based on the horseradish peroxidase (HRP)-like activity of the novel metal coordination polymer nanoparticles formed between Cu2+ and guanosine monophosphate (GMP), denoted as Cu-GMP CPNs, a label-free visual platform was constructed and successfully utilized for both self-correcting logic gate construction and sensitive biosensing. The HRP-mimicking ability of Cu-GMP CPNs was verified and utilized for the sensitive detection of both H2O2 and glucose. More importantly, a set of logic gates (AND, OR, NOR, INHIBIT, and XNOR) were fabricated, in which two intermediate outputs, i.e., color change and precipitate formation, were combined in an AND'' mode to produce the final output, and thus the as-proposed logic system exhibited the self-correction ability to automatically correct the erroneous intermediate outputs induced by interfering substances such as HRP. Moreover, in addition to the unique feature of self-correction, the as-proposed logic system also exhibited the advantages of simple operation, rapid response and easy detection of the visual outputs by the naked eye, thus expanding its practical applications to a variety of fields. Therefore, the label-free visual platform we have proposed here offers a promising strategy for logic gate fabrication and may pave the way for the development of novel molecular computing with self-correction abilities.