SERS Sensing of Dopamine with Fe(III)-Sensitized Nanogaps in Recleanable AuNP Monolayer Films

Sensing of neurotransmitters (NTs) down to nm concentrations is demonstrated by utilizing self-assembled monolayers of plasmonic 60 nm Au nanoparticles in close-packed arrays immobilized onto glass substrates. Multiplicative surface-enhanced Raman spectroscopy enhancements are achieved by integrating Fe(III) sensitizers into the precisely-defined <1 nm nanogaps, to target dopamine (DA) sensing. The transparent glass substrates allow for efficient access from both sides of the monolayer aggregate films by fluid and light, allowing repeated sensing in different analytes. Repeated reusability after analyte sensing is shown through oxygen plasma cleaning protocols, which restore pristine conditions for the nanogaps. Examining binding competition in multiplexed sensing of two catecholamine NTs, DA and epinephrine, reveals their bidentate binding and their interactions. These systems are promising for widespread microfluidic integration enabling a wide range of continuous biofluid monitoring for applications in precision health

Applying support-vector machine learning algorithms toward predicting host-guest interactions with cucurbit[7]uril.

Machine learning is a valuable tool in the development of chemical technologies but its applications into supramolecular chemistry have been limited. Here, the utility of kernel-based support vector machine learning using density functional theory calculations as training data is evaluated when used to predict equilibrium binding coefficients of small molecules with cucurbit[7]uril (CB[7]). We find that utilising SVMs may confer some predictive ability. This algorithm was then used to predict the binding of drugs TAK-580 and selumetinib. The algorithm did predict strong binding for TAK-580 and poor binding for selumetinib, and these results were experimentally validated. It was discovered that the larger homologue cucurbit[8]uril (CB[8]) is partial to selumetinib, suggesting an opportunity for tunable release by introducing different concentrations of CB[7] or CB[8] into a hydrogel depot. We qualitatively demonstrated that these drugs may have utility in combination against gliomas. Finally, mass transfer simulations show CB[7] can independently tune the release of TAK-580 without affecting selumetinib. This work gives specific evidence that a machine learning approach to recognition of small molecules by macrocycles has merit and reinforces the view that machine learning may prove valuable in the development of drug delivery systems and supramolecular chemistry more broadly.A.T. and M.P.S. thank The Winston Churchill Foundation of the United States. A.T. thanks the National Science Foundation graduate research fellowship, the MIT Chemical Engineering first year fellowship, and the Churchill College post-graduate grant program. G.W. thanks the Leverhulme Trust (project: ‘Natural material innovation for sustainable living’). V.K.R. thanks the Swiss National Science Foundation (P2EZP2_168784). O.A.S. acknowledges EPSRC Programme grant Nano-Optics to controlled Nano- Chemistry (NOtCH, EP/L027151/1) for funding

Plasmon-induced optical control over dithionite-mediated chemical redox reactions.

External-stimuli controlled reversible formation of radical species is of great interest for synthetic and supramolecular chemistry, molecular machinery, as well as emerging technologies ranging from (photo)catalysis and photovoltaics to nanomedicine. Here we show a novel hybrid colloidal system for light-driven reversible reduction of chemical species that, on their own, do not respond to light. This is achieved by the unique combination of photo-sensitive plasmonic aggregates and temperature-responsive inorganic species generating radicals that can be finally accepted and stabilised by non-photo-responsive organic molecules. In this system Au nanoparticles (NPs) self-assembled via sub-nm precise molecular spacers (cucurbit[n]urils) interact strongly with visible light to locally accelerate the decomposition of dithionite species (S2O42-) close to the NP interfaces. This light-driven process leads to the generation of inorganic radicals whose electrons can then be reversibly picked up by small organic acceptors, such as the methyl viologen molecules (MV2+) used here. During light-triggered plasmon- and heat-assisted generation of radicals, the S2O42- species work as a chemical 'fuel' linking photo-induced processes at the NP interfaces with redox chemistry in the surrounding water environment. By incorporating MV2+ as a Raman-active reporter molecule, the resulting optically-controlled redox processes can be followed in real-time.European commision: Marie Skłodowska-Curie funding, ERC, EPSRC, Leverhulme Trust, Newton Trust

SERS Sensing of Dopamine with Fe(III)-Sensitized Nanogaps in Recleanable AuNP Monolayer Films.

Sensing of neurotransmitters (NTs) down to nm concentrations is demonstrated by utilizing self-assembled monolayers of plasmonic 60 nm Au nanoparticles in close-packed arrays immobilized onto glass substrates. Multiplicative surface-enhanced Raman spectroscopy enhancements are achieved by integrating Fe(III) sensitizers into the precisely-defined <1 nm nanogaps, to target dopamine (DA) sensing. The transparent glass substrates allow for efficient access from both sides of the monolayer aggregate films by fluid and light, allowing repeated sensing in different analytes. Repeated reusability after analyte sensing is shown through oxygen plasma cleaning protocols, which restore pristine conditions for the nanogaps. Examining binding competition in multiplexed sensing of two catecholamine NTs, DA and epinephrine, reveals their bidentate binding and their interactions. These systems are promising for widespread microfluidic integration enabling a wide range of continuous biofluid monitoring for applications in precision health

Inhibiting Analyte Theft in Surface-Enhanced Raman Spectroscopy Substrates: Subnanomolar Quantitative Drug Detection.

Quantitative applications of surface-enhanced Raman spectroscopy (SERS) often rely on surface partition layers grafted to SERS substrates to collect and trap-solvated analytes that would not otherwise adsorb onto metals. Such binding layers drastically broaden the scope of analytes that can be probed. However, excess binding sites introduced by this partition layer also trap analytes outside the plasmonic "hotspots". We show that by eliminating these binding sites, limits of detection (LODs) can effectively be lowered by more than an order of magnitude. We highlight the effectiveness of this approach by demonstrating quantitative detection of controlled drugs down to subnanomolar concentrations in aqueous media. Such LODs are low enough to screen, for example, urine at clinically relevant levels. These findings provide unique insights into the binding behavior of analytes, which are essential when designing high-performance SERS substrates.In addition to the EPSRC funding B.d.N acknowledges support from the Leverhulme Trust and Isaac Newton Trust, C.C. acknowledges support from NPL (PO443073), R.C. acknowledges support from the Dr. Manmohan Singh scholarship from St. John’s College, M.K. thanks the European Commission for a Marie Skłodowska-Curie Fellowship (SPARCLEs, 7020005), S.J.B. thanks the European Commission for a Marie Skłodowska-Curie Fellowship (NANOSPHERE, 658360)