期刊
NANOSCALE
卷 8, 期 16, 页码 8591-8599出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/c6nr01072e
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类别
资金
- National Natural Science Foundation of China [21222507, 21575038, 21235002, 21175036]
- Foundation for Innovative Research Groups of NSFC [21521063]
- Natural Science Foundation of Hunan Province [2015JJ1005]
In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.
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