Biomimetic multienzyme nanocomplex for efficient cascade reactions

• Nanoscaled packing enzymes while preserving enzyme conformation is firstly reported. • This packing shortens intermediate transport distance and enhances cascade reaction. • The catalytic behavior of the packed enzymes is revealed. • Using the packed enzymes, glucose is detected with high sensitivity and selectivity. In nature, living cells form multienzyme complex by spatializing enzymes in confined compartments to enable cascade reactions. As these reactions are highly efficient and crucial to cellular metabolism, it is important to understand their catalytic behaviors. Herein, we report a living cell-inspired design of nanoscale multienzyme complex (nanocomplex), in which different enzymes are densely packed with intact conformations as the cellular multienzyme complex does, allowing sufficient transportation of intermedia and creating efficient cascade reactions. Benefit from the similarity between the proposed nanocomplex and cellular multienzyme complex, the systematic study of the effect of enzyme ratios and quantity to the nanocomplex reaction efficiency can inspire the investigation of the basic rules of cellular catalytic behaviors. In addition, the nanocomplex can also contribute to boosting the detection sensitivity of multienzyme-based biosensing due to its unsurpassed efficiency. Using the nanocomplex fabricated with methoxy polyethylene glycol (mPEG), glucose oxidase (GOx) and horseradish peroxidase (HRP), glucose in untreated urine, plasma and saliva samples can be detected with a remarkable detection limit of 1.6 µM and a detection time of just 30 s, surpass the current glucose detection approaches. Remarkably, the proposed sensor can also perform glucose detection with preserved cascade activity under high temperature, acid environment, or after long-time storage. Overall, this work can potentially provide a general understanding of multienzyme catalytic behaviors and a promising platform of ultrasensitive biosensing for disease diagnosis and prognosis.