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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.

Sensors for human health and performance monitoring require biological recognition elements (BREs) at device interfaces for the detection of key molecular biomarkers that are measurable biological state indicators. BREs, including peptides, antibodies, and nucleic acids, bind to biomarkers in the vicinity of the sensor surface to create a signal proportional to the biomarker concentration. The discovery of BREs with the required sensitivity and selectivity to bind biomarkers at low concentrations remains a fundamental challenge. In this study, we describe an in-silico approach to evolve higher sensitivity peptide-based BREs for the detection of cardiac event marker protein troponin I (cTnI) from a previously identified BRE as the parental affinity peptide. The P2 affinity peptide, evolved using our in-silico method, was found to have ∼16-fold higher affinity compared to the parent BRE and ∼10 fM (0.23 pg/mL) limit of detection. The approach described here can be applied towards designing BREs for other biomarkers for human health monitoring.

Understanding the factors that influence the interaction between biomolecules and abiotic surfaces is of utmost interest in biosensing and biomedical research. Through phage display technology, several peptides have been identified as specific binders to abiotic material surfaces, such as gold, graphene, silver, and so forth. Using graphene-peptide as our model abiotic-biotic pair, we investigate the effect of graphene quality, number of layers, and the underlying support substrate effect on graphene-peptide interactions using both experiments and computation. Our results indicate that graphene quality plays a significant role in graphene-peptide interactions. The graphene-biomolecule interaction appears to show no significant dependency on the number of graphene layers or the underlying support substrate.

In this work, to explain doping behavior of single-layer graphene upon HSSYWYAFNNKT (P1) and HSSAAAAFNNKT (P1-3A) adsorption in field-effect transistors (GFETs), we applied a combined computational approach, whereby peptide adsorption was modeled by molecular dynamics simulations, and the lowest energy configuration was confirmed by density functional theory calculations. On the basis of the resulting structures of the hybrid materials, electronic structure and transport calculations were investigated. We demonstrate that π-π stacking of the aromatic residues and proximate peptide backbone to the graphene surface in P1 have a role in the p-doping. These results are consistent with our experimental observation of the GFET's p-doping even after a 24-h annealing procedure. Upon substitution of three of the aromatic residues to Ala in (P1-3A), a considerable decrease from p-doping is observed experimentally, demonstrating n-doping as compared to the nonadsorbed device, yet not explained based on the atomistic MD simulation structures. To gain a qualitative understanding of P1-3A's adsorption over a longer simulation time, which may differ from aromatic amino acid residues' swift anchoring on the surface, we analyzed equilibrated coarse-grain simulations performed for 500 ns. Desorption of the Ala residues from the surface was shown computationally, which could in turn affect charge transfer, yet a full explanation of the mechanism of n-doping will require elucidation of differences between various aromatic residues as dependent on peptide composition, and inclusion of effects of the substrate and environment, to be considered in future work.

Noncovalent functionalization of graphene using peptides is a promising method for producing novel sensors with high sensitivity and selectivity. Here we perform atomic force microscopy, Raman spectroscopy, infrared spectroscopy, and molecular dynamics simulations to investigate peptide-binding behavior to graphene and graphite. We studied a dodecamer peptide identified with phage display to possess affinity for graphite. Optical spectroscopy reveals that the peptide forms secondary structures both in powder form and in an aqueous medium. The dominant structure in the powder form is α-helix, which undergoes a transition to a distorted helical structure in aqueous solution. The peptide forms a complex reticular structure upon adsorption on graphene and graphite, having a helical conformation different from α-helix due to its interaction with the surface. Our observation is consistent with our molecular dynamics calculations, and our study paves the way for rational functionalization of graphene using biomolecules with defined structures and, therefore, functionalities.

Peptides identified from combinatorial peptide libraries have been shown to bind to a variety of abiotic surfaces. Biotic-abiotic interactions can be exploited to create hybrid materials with interesting electronic, optical, or catalytic properties. Here we show that peptides identified from a combinatorial phage display peptide library assemble preferentially to the edge or planar surface of graphene and can affect the electronic properties of graphene. Molecular dynamics simulations and experiments provide insight into the mechanism of peptide binding to the graphene edge.

On the basis of their versatile structure and chemistry as well as tunable mechanical properties, polymer brushes are well-suited as supports for enzyme immobilization. However, a robust surface design is hindered by an inadequate understanding of the impact on activity from the coupling motif and enzyme distribution within the brush. Herein, horseradish peroxidase C (HRP C, 44 kDa), chosen as a model enzyme, was immobilized covalently through its lysine residues on a N-hydroxysuccinimidyl carbonate-activated poly(2-hydroxyethyl methacrylate) (PHEMA) brush grafted chemically onto a flat impenetrable surface. Up to a monolayer coverage of HRP C is achieved, where most of the HRP C resides at or near the brush-air interface. Molecular modeling shows that lysines 232 and 241 are the most probable binding sites, leading to an orientation of the immobilized HRP C that does not block the active pocket of the enzyme. Michaelis-Menten kinetics of the immobilized HRP C indicated little change in the K(m) (Michaelis constant) but a large decrease in the V(max) (maximum substrate conversion rate) and a correspondingly large decrease in the k(cat) (overall catalytic rate). This indicates a loss in the percentage of active enzymes. Given the relatively ideal geometry of the HRPC-PHEMA brush, the loss of activity is most likely due to structural changes in the enzyme arising from either secondary constraints imposed by the connectivity of the N-hydroxysuccinimidyl carbonate linking moiety or nonspecific interactions between HRP C and DSC-PHEMA. Therefore, a general enzyme-brush coupling motif must optimize reactive group density to balance binding with neutrality of surroundings.

Single-wall carbon nanotube field effect transistors (SWNT-FETs) are ideal candidates for fabricating sensors due to their unique electronic properties and have been widely investigated for chemical and biological sensing applications. The lack of selectivity of SWNT-FETs has prompted extensive research on developing ligands that exhibit specific binding as selective surface coating for SWNTs. Herein we describe the rational design of a peptide recognition element (PRE) that is capable of noncovalently attaching to SWNTs as well as binding to trinitrotoluene (TNT). The PRE contains two domains, a TNT binding domain derived from the binding pocket of the honeybee odor binding protein ASP1, and a SWNT binding domain previously identified from the phage peptide display library. The PRE structure in the presence of SWNT was investigated by performing classical all-atom molecular dynamics simulations, circular dichroism spectroscopy, and atomic force microscopy. Both computational and experimental analyses demonstrate that the peptide retains two functional domains for SWNT and TNT binding. The binding motif of the peptide to SWNT and to TNT was revealed from interaction energy calculations by molecular dynamics simulations. The potential application of the peptide for the detection of TNT is theoretically predicted and experimentally validated using a SWNT-FET sensor functionalized with a designer PRE. Results from this study demonstrate the creation of chemosensors using designed PRE as selective surface coatings for targeted analytes.

Single wall carbon nanotubes (SWNTs) have attracted attention because of their potential in a vast range of applications, including transistors and sensors. However, immense technological importance lies in enhancing the purity and homogeneity of SWNTs with respect to their chirality for real-world electronic applications. In order to achieve optimal performance of SWNTs, the diameter, type, and chirality have to be effectively sorted. Any employed strategy for sorting SWNTs has to be scalable, nondestructible, and economical. In this paper, we present a solubilization and chirality enrichment study of commercially available SWNTs using genomic DNA. On the basis of the comparison of the photoluminescence (PL) and near-infrared absorption measurements from the SWNTs dispersed with salmon genomic DNA (SaDNA) and d(GT)20, we show that genomic DNA specifically enriches (6,5) tubes. Circular dichroism and classical all-atom molecular dynamics simulations reveal that the genomic double-stranded SaDNA prefers to interact with (6,5) SWNTs as compared to (10,3) tubes, meanwhile single-stranded d(GT)20 shows no or minimal chirality preference. Our enrichment process demonstrates enrichment of >86% of (6,5) SWNTs from CoMoCat nanotubes using SaDNA.