Recognition-driven layer-by-layer construction of multiprotein assemblies on surfaces: a biomolecular toolkit for...

The development of soft bioelectronic interfaces with accurate compositional and topological control of the supramolecular architecture attracts intense interest in the fast-growing field of bioelectronics and biosensing. The present study explores the recognition-driven layer-by-layer assembly of glycoenzymes onto electrode surfaces. The design of the multi-protein interfacial architecture is based on the multivalent supramolecular carbohydrate-lectin interactions between redox glycoproteins and concanavalin A (Con A) derivatives. Specifically, [Os(bpy)(2)Clpy](2+)-tagged Con A (Os-Con A) and native Con A were used to direct the assembly of horseradish peroxidase (HRP) and glucose oxidase (GOx) in a stepwise topologically controlled procedure. In our designed configuration, GOx acts as the biorecognition element to glucose stimulus, while HRP acts as the transducing element. Surface plasmon resonance (SPR) spectroscopy and quartz crystal microbalance with dissipation (QCM-D) results are combined to give a close representation of the protein surface coverage and the content of water in the protein assembly. The characterization is complemented with in situ atomic force microscopy (AFM) to give a topographical description of the layers assemblage. Electrochemical (EC) techniques were used to characterize the functional features of the spontaneously self-assembled biohybrid architecture, showing that the whole system presents efficient electron transfer and mass transport processes being able to transform micromolar glucose concentration into electrical information. In this way the combination of the electroactive and nonelectroactive Con A provides an efficient strategy to control the position and composition of the protein layers via recognition-driven processes, which defines its sensitivity toward glucose. Furthermore, the incorporation of dextran as a permeable interlayer able to bind Con A promotes the physical separation of the biochemical and transducing processes, thus enhancing the magnitude of the bioelectrochemical signal. We consider that these results are relevant for the nanoconstruction of functional biointerfaces provided that our experimental evidence reveals the possibility of locally addressing recognition, transduction and amplification elements in interfacial ensembles via LbL recognition-driven processes.