Label-free surface-enhanced Raman spectroscopy (SERS) can interrogate systems by directly fingerprinting their components' unique physicochemical properties. In complex biological systems however, this can yield highly overlapping spectra that hinder sample identification. Here, we present an artificial-nose inspired SERS fingerprinting approach where spectral data is obtained as a function of sensor surface chemical functionality. Supported by molecular dynamics modeling, we show that mildly selective self-assembled monolayers can influence the strength and configuration in which analytes interact with plasmonic surfaces, diversifying the resulting SERS fingerprints. Since each sensor generates a modulated signature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates for all possible combinations of up to 9 fingerprints. Reliable improvements in mean discriminatory accuracy towards 100% are achieved with each additional surface functionality. This arrayed label-free platform illustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for more reliable assessment of complex biological matrices.

Quantum-sized metallic clusters protected by biological ligands represent a new class of luminescent materials; yet the understanding of structural information and photoluminescence origin of these ultra-small clusters remains a challenge. Herein we systematically study the surface ligand dynamics and and ligand-metal core interactions of peptide-protected gold nanoclusters (AuNCs) with combined experimental characterizations and theoretical molecular simulations. We propose that the emission brightness of the resultant nanoclusters is determined by the surface peptide structuring, interfacial water dynamics and ligand-Au core interaction, which can be tailored by controlling peptide acetylation, constituent amino acid electron donating/withdrawing capacity, aromaticity/hydrophobicity and by adjusting environmental pH. Specifically, emission enhancement is achieved through increasing the electron density of surface ligands in proximity to the Au core, discouraging photo-induced quenching, and by reducing the amount of surface-bound water molecules. These findings provide key design principles for maximizing the photoluminescence of metallic clusters through the exploitation of biologically relevant ligand properties.

Gold nanoparticles (AuNPs) are an integral part of many exciting and novel biomedical applications, sparking the urgent need for a thorough understanding of the physicochemical interactions occurring between these inorganic materials, their functional layers, and the biological species they interact with. Computational approaches are instrumental in providing the necessary molecular insight into the structural and dynamic behavior of the Au-bio interface with spatial and temporal resolutions not yet achievable in the laboratory, and are able to facilitate a rational approach to AuNP design for specific applications. A perspective of the current successes and challenges associated with the multiscale computational treatment of Au-bio interfacial systems, from electronic structure calculations to force field methods, is provided to illustrate the links between different approaches and their relationship to experiment and applications.

In this study we investigate, using all-atom Molecular-Dynamics computer simulations, the in-plane diffusion of a doxorubicin drug molecule in a thin film of water confined between two silica surfaces. We...