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Recognition and manipulation of graphene edges enable the control of physical properties of graphene-based devices. Recently, the authors have identified a peptide that preferentially binds to graphene edges from a combinatorial peptide library. In this study, the authors examine the functional basis for the edge binding peptide using experimental and computational methods. The effect of amino acid substitution, sequence context, and solution pH value on the binding of the peptide to graphene has been investigated. The N-terminus glutamic acid residue plays a key role in recognizing and binding to graphene edges. The protonation, substitution, and positional context of the glutamic acid residue impact graphene edge-binding. Our findings provide insights into the binding mechanisms and the design of peptides for recognizing and functionalizing graphene edges. [ABSTRACT FROM AUTHOR]

Wearable sensors for human health, performance, and state monitoring, which have a linear response to the binding of biomarkers found in sweat, saliva, or urine, are of current interest for many applications. A critical part of any device is a biological recognition element (BRE) that is able to bind a biomarker at the surface of a sensor with a high affinity and selectivity to produce a measurable signal response. In this study, we discover and compare 12-mer peptides that bind to neuropeptide Y (NPY), a stress and human health biomarker, using independent and complimentary experimental and computational approaches. The affinities of the NPY-binding peptides discovered by both methods are equivalent and below the micromolar level, which makes them suitable for application in sensors. The in silico design protocol for peptide-based BREs is low cost, highly efficient, and simple, suggesting its utility for discovering peptide binders to a variety of biomarker targets.