Computational Insights into the Adsorption of Ligands on Gold Nanosurfaces

We study the adsorption process of model peptides, nucleobases, and selected standard ligands on gold through the development of a computational protocol based on fully atomistic classical molecular dynamics (MD) simulations combined with umbrella sampling techniques. The specific features of the interface components, namely, the molecule, the metallic substrate, and the solvent, are taken into account through different combinations of force fields (FFs), which are found to strongly affect the results, especially changing absolute and relative adsorption free energies and trends. Overall, noncovalent interactions drive the process along the adsorption pathways. Our findings also show that a suitable choice of the FF combinations can shed light on the affinity, position, orientation, and dynamic fluctuations of the target molecule with respect to the surface. The proposed protocol may help the understanding of the adsorption process at the microscopic level and may drive the in-silico design of biosensors for detection purposes.

Rapidly determining the 3D structure of proteins by surface-enhanced Raman spectroscopy

Despite great advances in protein structure analysis, label-free and ultrasensitive methods to obtain the natural and dynamic three-dimensional (3D) structures are still urgently needed. Surface-enhanced Raman spectroscopy (SERS) can be a good candidate, whereas the complexity originated from the interactions between the protein and the gradient surface electric field makes it extremely challenging to determine the protein structure. Here, we propose a deciphering strategy for accurate determination of 3D protein structure from experimental SERS spectra in seconds by simply summing SERS spectra of isolated amino acids in electric fields of different strength with their orientations in protein. The 3D protein structure can be reconstructed by comparing the experimental spectra obtained in a well-defined gap-mode SERS configuration with the simulated spectra. The gradient electric field endows SERS with a unique advantage to section biomolecules with atomic precision, which makes SERS a competent tool for monitoring biomolecular events under physiological conditions.

Gaussian attractive potential for carboxylate/cobalt surface interactions

Ligand-decorated metal surfaces play a pivotal role in various areas of chemistry, particularly in selective catalysis. Molecular dynamics simulations at the molecular mechanics level of theory are best adapted to gain complementary insights to experiments regarding the structure and dynamics of such organic films. However, standard force fields tend to capture only weak physisorption interactions. This is inadequate for ligands that are strongly adsorbed such as carboxylates on metal surfaces. To address this limitation, we employ the Gaussian Lennard-Jones (GLJ) potential, which incorporates an attractive Gaussian potential between the surface and ligand atoms. Here, we develop this approach for the interaction between cobalt surfaces and carboxylate ligands. The accuracy of the GLJ approach is validated through the analysis of the interaction of oxygen with two distinct cobalt surfaces. The accuracy of this method reaches a root mean square deviation (RMSD) of about 3 kcal/mol across all probed configurations, which corresponds to a percentage error of roughly 4%. Application of the GLJ force field to the dynamics of the organic layer on these surfaces reveals how the ligand concentration influences the film order, and highlights differing mobility in the x and y directions, attributable to surface corrugation on Co(112̄0). GLJ is versatile, suitable for a broad range of metal/ligand systems, and can, subsequently, be utilized to study the organic film on the adsorption/desorption of reactants and products during a catalytic process.

Electrochemistry in sensing of molecular interactions of proteins and their behavior in an electric field

Electrochemical methods can be used not only for the sensitive analysis of proteins but also for deeper research into their structure, transport functions (transfer of electrons and protons), and sensing their interactions with soft and solid surfaces. Last but not least, electrochemical tools are useful for investigating the effect of an electric field on protein structure, the direct application of electrochemical methods for controlling protein function, or the micromanipulation of supramolecular protein structures. There are many experimental arrangements (modalities), from the classic configuration that works with an electrochemical cell to miniaturized electrochemical sensors and microchip platforms. The support of computational chemistry methods which appropriately complement the interpretation framework of experimental results is also important. This text describes recent directions in electrochemical methods for the determination of proteins and briefly summarizes available methodologies for the selective labeling of proteins using redox-active probes. Attention is also paid to the theoretical aspects of electron transport and the effect of an external electric field on the structure of selected proteins. Instead of providing a comprehensive overview, we aim to highlight areas of interest that have not been summarized recently, but, at the same time, represent current trends in the field.

Deconstructing Electrostatics of Functionalized Metal Nanoparticles from Molecular Dynamics Simulations

Gold nanoparticles (NPs) with different surface functionalizations can selectively interact with specific proteins, allowing a wide range of possible applications in biotechnology and biomedicine. To prevent their tendency to aggregate and to modulate their interaction with charged biomolecules or substrates (e.g., for biosensing applications), they can be functionalized with charged groups, introducing a mutual interaction which can be modulated by changing the ionic strength of the solvent. In silico modeling of these systems is often addressed with low-resolution models, which must account for these effects in the, often implicit, solvent representation. Here, we present a systematic conformational dynamic characterization of ligand-coated gold nanoparticles with different sizes, charges, and functionalizations by means of atomistic molecular dynamics simulations. Based on these, we deconstruct their electrostatic properties and propose a general representation of their average-long-range interactions extendable to different sizes, charges, and ionic strengths. This study clarifies in detail the role of the different features of the NP (charge, size, structure) and of the ionic strength in determining the details of the interparticle interaction and represents the first step toward a general strategy for the parametrization of NP coarse-grained models able to account for varying ionic strengths.

Theory and Simulations of Ionic Liquids in Nanoconfinement

Room-temperature ionic liquids (RTILs) have exciting properties such as nonvolatility, large electrochemical windows, and remarkable variety, drawing much interest in energy storage, gating, electrocatalysis, tunable lubrication, and other applications. Confined RTILs appear in various situations, for instance, in pores of nanostructured electrodes of supercapacitors and batteries, as such electrodes increase the contact area with RTILs and enhance the total capacitance and stored energy, between crossed cylinders in surface force balance experiments, between a tip and a sample in atomic force microscopy, and between sliding surfaces in tribology experiments, where RTILs act as lubricants. The properties and functioning of RTILs in confinement, especially nanoconfinement, result in fascinating structural and dynamic phenomena, including layering, overscreening and crowding, nanoscale capillary freezing, quantized and electrotunable friction, and superionic state. This review offers a comprehensive analysis of the fundamental physical phenomena controlling the properties of such systems and the current state-of-the-art theoretical and simulation approaches developed for their description. We discuss these approaches sequentially by increasing atomistic complexity, paying particular attention to new physical phenomena emerging in nanoscale confinement. This review covers theoretical models, most of which are based on mapping the problems on pertinent statistical mechanics models with exact analytical solutions, allowing systematic analysis and new physical insights to develop more easily. We also describe a classical density functional theory, which offers a reliable and computationally inexpensive tool to account for some microscopic details and correlations that simplified models often fail to consider. Molecular simulations play a vital role in studying confined ionic liquids, enabling deep microscopic insights otherwise unavailable to researchers. We describe the basics of various simulation approaches and discuss their challenges and applicability to specific problems, focusing on RTIL structure in cylindrical and slit confinement and how it relates to friction and capacitive and dynamic properties of confined ions.

Tunneling-to-Hopping Transition in Multiheme Cytochrome Bioelectronic Junctions

Multiheme cytochromes (MHCs) have attracted much interest for use in nanobioelectronic junctions due to their high electronic conductances. Recent measurements on dry MHC junctions suggested that a coherent tunneling mechanism is operative over surprisingly long long distances (>3 nm), which challenges our understanding of coherent transport phenomena. Here we show that this is due to (i) a low exponential distance decay constant for coherent conduction in MHCs (β = 0.2 Å^-1) and (ii) a large density of protein electronic states which prolongs the coherent tunneling regime to distances that exceed those in molecular wires made of small molecules. Incoherent hopping conduction is uncompetitive due to the large energy level offset at the protein-electrode interface. Removing this offset, e.g., by gating, we predict that the transport mechanism crosses over from coherent tunneling to incoherent hopping at a protein size of ∼7 nm, thus enabling transport on the micrometer scale with a shallow polynomial (∼1/r) distance decay.

Tuning gold-based surface functionalization for streptavidin detection: A combined simulative and experimental study

A rationally designed gold-functionalized surface capable of capturing a target protein is presented using the biotin–streptavidin pair as a proof-of-concept. We carried out multiscale simulations to shed light on the binding mechanism of streptavidin on four differently biotinylated surfaces. Brownian Dynamics simulations were used to reveal the preferred initial orientation of streptavidin over the surfaces, whereas classical molecular dynamics was used to refine the binding poses and to investigate the fundamental forces involved in binding, and the binding kinetics. We assessed the binding events and the stability of the streptavidin attachment through a quartz crystal microbalance with dissipation monitoring (QCM-D). The sensing element comprises of biotinylated polyethylene glycol chains grafted on the sensor’s gold surface via thiol-Au chemistry. Finally, we compared the results from experiments and simulations. We found that the confined biotin moieties can specifically capture streptavidin from the liquid phase and provide guidelines on how to exploit the microscopic parameters obtained from simulations to guide the design of further biosensors with enhanced sensitivity.

Predicting protein function and orientation on a gold nanoparticle surface using a residue-based affinity scale

The orientation adopted by proteins on nanoparticle surfaces determines the nanoparticle's bioactivity and its interactions with living systems. Here, we present a residue-based affinity scale for predicting protein orientation on citrate-gold nanoparticles (AuNPs). Competitive binding between protein variants accounts for thermodynamic and kinetic aspects of adsorption in this scale. For hydrophobic residues, the steric considerations dominate, whereas electrostatic interactions are critical for hydrophilic residues. The scale rationalizes the well-defined binding orientation of the small GB3 protein, and it subsequently predicts the orientation and active site accessibility of two enzymes on AuNPs. Additionally, our approach accounts for the AuNP-bound activity of five out of six additional enzymes from the literature. The model developed here enables high-throughput predictions of protein behavior on nanoparticles, and it enhances our understanding of protein orientation in the biomolecular corona, which should greatly enhance the performance and safety of nanomedicines used in vivo.

Beyond single-crystal surfaces: The GAL21 water/metal force field

Solvent effects are notoriously difficult to describe for metallic nanoparticles (NPs). Here, we introduce GAL21 which is the first pairwise additive force field that is specifically designed to modulate the near chemisorption energy of water as a function of the coordination numbers of the metallic atoms. We find a quadratic dependence to be most suitable for capturing the dependence of the adsorption energy of water on the generalized coordination number (GCN) of the metal atoms. GAL21 has been fitted against DFT adsorption energies for Cu, Ag, Au, Ni, Pd, Pt, and Co on 500 configurations and validated on about 3000 configurations for each metal, constructed on five surfaces with GCNs varying from 2.5 to 11.25. Depending on the metals, the root mean square deviation is found between 0.7 kcal mol−1 (Au) to 1.6 kcal mol−1 (Ni). Using GAL21, as implemented in the open-source code CP2K, we then evaluate the solvation energy of Au55 and Pt55 NPs in water using thermodynamic integration. The solvation free energy is found to be larger for Pt than for Au and systematically larger than 200 kcal mol−1, demonstrating the large impact of solvent on the surface energetics of NPs. Still, given that the amorphous NPs are both, the most stable and the most solvated ones, we do not predict a change in the preferred morphology between the gas-phase and in water. Finally, based on a linear regression on three sizes of NPs (from 38 to 147), the solvation energy for Au and Pt surface atoms is found to be −5.2 and −9.9 kcal mol−1, respectively.

Mechanistic insights into the size-dependent effects of nanoparticles on inhibiting and accelerating amyloid fibril formation

The aggregation of peptides into amyloid fibrils has been linked to ageing-related diseases, such as Alzheimer's and type 2 diabetes. Interfaces, particularly those with large nanostructured surfaces, can affect the kinetics of peptide aggregation, which ranges from complete inhibition to strong acceleration. While a number of physiochemical parameters determine interfacial effects, we focus here on the role of nanoparticle (NP) size and curvature. We used thioflavin T (ThT) fluorescence assays to demonstrate the size-dependent effects of NPs on amyloid fibril formation for the peptides Aβ₄₀, NNFGAIL, GNNQQNY and VQIYVK. While 5 nm gold NPs (AuNP-5) retarded or inhibited the aggregation of all peptides except NNFGAIL, larger 20 nm gold NPs (AuNP-20) tended to accelerate or not influence peptide aggregation. Differences in the NP effects for the peptides resulted from the different peptide properties (size, tendency to aggregate) and associated surface binding affinities. Additional dynamic light scattering (DLS), electron microscopy, and atomic force microscopy (AFM) experiments with the Aβ₄₀ peptide confirmed size-dependent NP effects on peptide aggregation, and also suggested a structural influence on the formed fibrils. NPs can serve as a surface for the adsorption of peptide monomers and enable nucleation to oligomers and fibril formation. However, molecular dynamics (MD) simulations showed that peptide oligomers were less stable at smaller NPs. High surface curvatures destabilized prefibrillar structures, which provides a possible explanation for inhibitory effects on fibril growth, provided that peptide-NP surface binding was relevant for fibril formation. These mechanistic insights can support the design of future nanostructured materials.

Peptide adsorption on silica surfaces: Simulation and experimental insights

The understanding of interactions between proteins with silica surface is crucial for a wide range of different applications: from medical devices, drug delivery and bioelectronics to biotechnology and downstream processing. We show the application of EISM (Effective Implicit Surface Model) for discovering the set of peptide interactions with silica surface. The EISM is employed for a high-speed computational screening of peptides to model the binding affinity of small peptides to silica surfaces. The simulations are complemented with experimental data of peptides with silica nanoparticles from microscale thermophoresis and from infrared spectroscopy. The experimental work shows excellent agreement with computational results and verifies the EISM model for the prediction of peptide-surface interactions. 57 peptides, with amino acids favorable for adsorption on Silica surface, are screened by EISM model for obtaining results, which are worth to be considered as a guidance for future experimental and theoretical works. This model can be used as a broad platform for multiple challenges at surfaces which can be applied for multiple surfaces and biomolecules beyond silica and peptides.

Molecular Driving Force for Facet Selectivity of Sequence-Defined Amphiphilic Peptoids at Au-Water Interfaces

Shape-controlled colloidal nanocrystal syntheses often require facet-selective solution-phase chemical additives to regulate surface free energy, atom addition/migration fluxes, or particle attachment rates. Because of their highly tunable properties and robustness to a wide range of experimental conditions, peptoids represent a very promising class of next-generation functional additives for control over nanocrystal growth. However, understanding the origin of facet selectivity at the molecular level is critical to generalizing their design. Herein we employ molecular dynamics simulations and biased sampling methods and report stronger selectivity to Au(111) than to Au(100) for Nce3Ncp6, a peptoid that has been shown to assist the formation of 5-fold twinned Au nanostars. We find that facet selectivity is achieved through synergistic effects of both peptoid-surface and solvent-surface interactions. Moreover, the amphiphilic nature of Nce3Ncp6 together with the order of peptoid-peptoid and peptoid-surface binding energies, that is, peptoid-Au(100) < peptoid-peptoid < peptoid-Au(111), further amplifies its distinct collective behavior on different Au surfaces. Our studies provide a fundamental understanding of the molecular origin of facet-selective adsorption and highlight the possibility of future designs and uses of sequence-defined peptoids for predictive syntheses of nanocrystals with designed shapes and properties.

Curvature and temperature-dependent thermal interface conductance between nanoscale-gold and water

<p>Plasmonic gold nanoparticles (AuNPs) can convert laser irradiation into thermal energy for a variety of applications. Although heat transfer through the AuNP-water interface is considered an essential part of the plasmonic heating process, there is a lack of mechanistic understanding of how interface curvature and the heating itself impact interfacial heat transfer. Here, we report atomistic molecular dynamics simulations that investigate heat transfer through nanoscale gold-water interfaces. We simulated four nanoscale gold structures under various applied heat flux to evaluate how gold-water interface curvature and temperature affect the interfacial heat transfer. We also considered a case in which we artificially reduced wetting at the gold surfaces by tuning the gold-water interactions to determine if such a perturbation alters the curvature and temperature dependence of the gold-water interfacial heat transfer. We first confirmed that interfacial heat transfer is particularly important for small particles (diameter {less than or equal to} 10 nm). We found that the thermal interface conductance increases linearly with interface curvature regardless of the gold wettability, while it increases non-linearly with the applied heat flux under normal wetting and remains constant under reduced wetting. Our analysis suggests the curvature dependence of the interface conductance coincides with changes in interfacial water adsorption, while the temperature dependence may arise from temperature-induced shifts in the distribution of water vibrational states. Our study advances the current understanding of interface thermal conductance for a broad range of applications.

Flexible Superlubricity Unveiled in Sidewinding Motion of Individual Polymeric Chains

A combination of low temperature atomic force microcopy and molecular dynamic simulations is used to demonstrate that soft designer molecules realize a sidewinding motion when dragged over a gold surface. Exploiting their longitudinal flexibility, pyrenylene chains are indeed able to lower diffusion energy barriers via on-surface directional locking and molecular strain. The resulting ultralow friction reaches values on the order of tens of pN reported so far only for rigid chains sliding on an incommensurate surface. Therefore, we demonstrate how molecular flexibility can be harnessed to realize complex nanomotion while retaining a superlubric character. This is in contrast with the paradigm guiding the design of most superlubric nanocontacts (mismatched rigid contacting surfaces).

Engineering the Aggregation of Dyes on Ligand-Shell Protected Gold Nanoparticles to Promote Plexcitons Formation

The ability to control the light–matter interaction in nanosystems is a major challenge in the field of innovative photonics applications. In this framework, plexcitons are promising hybrid light–matter states arising from the strong coupling between plasmonic and excitonic materials. However, strategies to precisely control the formation of plexcitons and to modulate the coupling between the plasmonic and molecular moieties are still poorly explored. In this work, the attention is focused on suspensions of hybrid nanosystems prepared by coupling cationic gold nanoparticles to tetraphenyl porphyrins in different aggregation states. The role of crucial parameters such as the dimension of nanoparticles, the pH of the solution, and the ratio between the nanoparticles and dye concentration was systematically investigated. A variety of structures and coupling regimes were obtained. The rationalization of the results allowed for the suggestion of important guidelines towards the control of plexcitonic systems.

High affinity protein surface binding through co-engineering of nanoparticles and proteins

Control over supramolecular recognition between proteins and nanoparticles (NPs) is of fundamental importance in therapeutic applications and sensor development. Most NP-protein binding approaches use 'tags' such as biotin or His-tags to provide high affinity; protein surface recognition provides a versatile alternative strategy. Generating high affinity NP-protein interactions is challenging however, due to dielectric screening at physiological ionic strengths. We report here the co-engineering of nanoparticles and protein to provide high affinity binding. In this strategy, 'supercharged' proteins provide enhanced interfacial electrostatic interactions with complementarily charged nanoparticles, generating high affinity complexes. Significantly, the co-engineered protein-nanoparticle assemblies feature high binding affinity even at physiologically relevant ionic strength conditions. Computational studies identify both hydrophobic and electrostatic interactions as drivers for these high affinity NP-protein complexes.

Atomistic Simulations of Functionalized Nano-Materials for Biosensors Applications

Nanoscale biosensors, a highly promising technique in clinical analysis, can provide sensitive yet label-free detection of biomolecules. The spatial and chemical specificity of the surface coverage, the proper immobilization of the bioreceptor as well as the underlying interfacial phenomena are crucial elements for optimizing the performance of a biosensor. Due to experimental limitations at the microscopic level, integrated cross-disciplinary approaches that combine in silico design with experimental measurements have the potential to present a powerful new paradigm that tackles the issue of developing novel biosensors. In some cases, computational studies can be seen as alternative approaches to assess the microscopic working mechanisms of biosensors. Nonetheless, the complex architecture of a biosensor, associated with the collective contribution from "substrate-receptor-analyte" conjugate in a solvent, often requires extensive atomistic simulations and systems of prohibitive size which need to be addressed. In silico studies of functionalized surfaces also require ad hoc force field parameterization, as existing force fields for biomolecules are usually unable to correctly describe the biomolecule/surface interface. Thus, the computational studies in this field are limited to date. In this review, we aim to introduce fundamental principles that govern the absorption of biomolecules onto functionalized nanomaterials and to report state-of-the-art computational strategies to rationally design nanoscale biosensors. A detailed account of available in silico strategies used to drive and/or optimize the synthesis of functionalized nanomaterials for biosensing will be presented. The insights will not only stimulate the field to rationally design functionalized nanomaterials with improved biosensing performance but also foster research on the required functionalization to improve biomolecule-surface complex formation as a whole.

Predicting Biomolecule Adsorption on MoS2 Nanosheets with High Structural Fidelity

A new force field, MoSu-CHARMM, for the description of bio-interfacial structures at the aqueous MoS2 interface is developed, based on quantum chemical data. The force field describes non-covalent interactions between...

First-Principles Modeling of Protein/Surface Interactions. Polyglycine Secondary Structure Adsorption on the TiO2 (101) Anatase Surface Adopting a Full Periodic Approach

Computational modeling of protein/surface systems is challenging since the conformational variations of the protein and its interactions with the surface need to be considered at once. Adoption of first-principles methods to this purpose is overwhelming and computationally extremely expensive so that, in many cases, dramatically simplified systems (e.g., small peptides or amino acids) are used at the expenses of modeling nonrealistic systems. In this work, we propose a cost-effective strategy for the modeling of peptide/surface interactions at a full quantum mechanical level, taking the adsorption of polyglycine on the TiO₂ (101) anatase surface as a test case. Our approach is based on applying the periodic boundary conditions for both the surface model and the polyglycine peptide, giving rise to full periodic polyglycine/TiO₂ surface systems. By proceeding this way, the considered complexes are modeled with a drastically reduced number of atoms compared with the finite-analogous systems, modeling the polypeptide structures at the same time in a realistic way. Within our modeling approach, full periodic density functional theory calculations (including implicit solvation effects) and ab initio molecular dynamics (AIMD) simulations at the PBE-D2* theory level have been carried out to investigate the adsorption and relative stability of the different polyglycine structures (i.e., extended primary, β-sheet, and α-helix) on the TiO₂ surface. It has been found that, upon adsorption, secondary structures become partially denatured because the peptide C═O groups form Ti-O═C dative bonds. AIMD simulations have been fundamental to identify these phenomena because thermal and entropic effects are of paramount importance. Irrespective of the simulated environments (gas phase and implicit solvent), adsorption of the α-helix is more favorable than that of the β-sheet because in the former, more Ti-O═C bonds are formed and the adsorbed secondary structure results less distorted with respect to the isolated state. Under the implicit water solvent, additionally, adsorbed β-sheet structures weaken with respect to their isolated states as the H-bonds between the strands are longer due to solvation effects. Accordingly, the results indicate that the preferred conformation upon adsorption is the α-helix over the β-sheet.

Molecular dynamics simulation study of gold nanosheet as drug delivery vehicles for anti-HIV-1 aptamers

The adsorption process of three aptamers with gold nanosheet (GNS) as a drug carrier has been investigated with the help of molecular dynamics simulations. The sequencing of the considered aptamers are as (CUUCAUUGUAACUUCUCAUAAUUUCCCGAGGCUUUUACUUUCGGGGUCCU) and (CCGGGUCGUCCCCUACGGGGACUAAAGACUGUGUCCAACCGCCCUCGCCU) for AP1 and AP2, respectively. AP3 is a muted version of AP1 in which nucleotide positions 4, 6, 18, 28 and 39 have C4A, U6G, A18G, G28A, and U39C mutations. At positions 24, and 40, a deletion mutation is seen to eliminate U24 and U40 bases. These aptamers are inhibitors for HIV-1 protease and can be candidates as potential pharmaceutics for treatment of AIDS in the future. The interactions between considered aptamers and GNS have been analyzed in detail with help of structural and energetic properties. These analyses showed that all three aptamers could well adsorb on GNS. Overall, the final results show that the adsorption of AP2 on the GNS is more favorable than other considered ones and consequently GNS can be considered as a device in order to immobilize these aptamers.

Theoretical and Experimental Elucidation of the Adsorption Process of a Bioinspired Peptide on Mineral Surfaces

Inorganic materials used for biomedical applications such as implants generally induce the adsorption of proteins on their surface. To control this phenomenon, the bioinspired peptidomimetic polymer 1 (PMP1), which aims to reproduce the adhesion of mussel foot proteins, is commonly used to graft specific proteins on various surfaces and to regulate the interfacial mechanism. To date and despite its wide application, the elucidation at the atomic scale of the PMP1 mechanism of adsorption on surfaces is still unknown. The purpose of the present work was thus to unravel this process through experimental and computational investigations of adsorption of PMP1 on gold, TiO₂, and SiO₂ surfaces. A common mechanism of adsorption is identified for the adsorption of PMP1 which emphasizes the role of electrostatics to approach the peptide onto the surface followed by a full adhesion process where the entropic desolvation step plays a key role. Besides, according to the fact that mussel naturally controls the oxidation states of its proteins, further investigations were performed for two distinct redox states of PMP1, and we conclude that even if both states are able to allow interaction of PMP1 with the surfaces, the oxidation of PMP1 leads to a stronger interaction.

Modelling peptide adsorption energies on gold surfaces with an effective implicit solvent and surface model

The interaction of proteins and peptides with inorganic surfaces is relevant in a wide array of technological applications. A rational approach to design peptides for specific surfaces would build on amino-acid and surface specific interaction models, which are difficult to characterize experimentally or by modeling. Even with such a model at hand, the large number of possible sequences and the large conformation space of peptides make comparative simulations challenging. Here we present a computational protocol, the effective implicit surface model (EISM), for efficient in silico evaluation of the binding affinity trends of peptides on parameterized surface, with a specific application to the widely studied gold surface. In EISM the peptide surface interactions are modeled with an amino-acid and surface specific implicit solvent model, which permits rapid exploration of the peptide conformational degrees of freedom. We demonstrate the parametrization of the model and compare the results with all-atom simulations and experimental results for specific peptides.

Sensing Enzyme Activation Heat Capacity at the Single-Molecule Level Using Gold-Nanorod-Based Optical Whispering Gallery Modes

Here, we report a label-free gold nanoparticle-based single-molecule optical platform to study the immobilization, activity, and thermodynamics of single enzymes. The sensor uses plasmonic gold nanoparticles coupled to optical whispering gallery modes (WGMs) to probe enzyme conformational dynamics during turnover at a microsecond time resolution. Using a glucosidase enzyme as the model system, we explore the temperature dependence of the enzyme turnover at the single-molecule (SM) level. A recent physical model for understanding enzyme temperature dependencies (macromolecular rate theory; MMRT) has emerged as a powerful tool to study the relationship between enzyme turnover and thermodynamics. Using WGMs, SM enzyme measurements enable us to accurately track turnover as a function of conformational changes and therefore to quantitatively probe the key feature of the MMRT model, the activation heat capacity, at the ultimate level of SM. Our data shows that WGMs are extraordinarily sensitive to protein conformational change and can discern both multiple steps with turnover as well as microscopic conformational substates within those steps. The temperature dependence studies show that the MMRT model can be applied to a range of steps within turnover at the SM scale that is associated with conformational change. Our study validates the notion that MMRT captures differences in dynamics between states. The WGM sensors provide a platform for the quantitative analysis of SM activation heat capacity, applying MMRT to the label-free sensing of microsecond substates of active enzymes.

Molecular Simulation of Electrode-Solution Interfaces

Many key industrial processes, from electricity production, conversion, and storage to electrocatalysis or electrochemistry in general, rely on physical mechanisms occurring at the interface between a metallic electrode and an electrolyte solution, summarized by the concept of an electric double layer, with the accumulation/depletion of electrons on the metal side and of ions on the liquid side. While electrostatic interactions play an essential role in the structure, thermodynamics, dynamics, and reactivity of electrode-electrolyte interfaces, these properties also crucially depend on the nature of the ions and solvent, as well as that of the metal itself. Such interfaces pose many challenges for modeling because they are a place where quantum chemistry meets statistical physics. In the present review, we explore the recent advances in the description and understanding of electrode-electrolyte interfaces with classical molecular simulations, with a focus on planar interfaces and solvent-based liquids, from pure solvent to water-in-salt electrolytes.

Molecular Dynamics Simulations of a Catalytic Multivalent Peptide-Nanoparticle Complex

Molecular modeling of a supramolecular catalytic system is conducted resulting from the assembling between a small peptide and the surface of cationic self-assembled monolayers on gold nanoparticles, through a multiscale iterative approach including atomistic force field development, flexible docking with Brownian Dynamics and µs-long Molecular Dynamics simulations. Self-assembly is a prerequisite for the catalysis, since the catalytic peptides do not display any activity in the absence of the gold nanocluster. Atomistic simulations reveal details of the association dynamics as regulated by defined conformational changes of the peptide due to peptide length and sequence. Our results show the importance of a rational design of the peptide to enhance the catalytic activity of peptide-nanoparticle conjugates and present a viable computational approach toward the design of enzyme mimics having a complex structure-function relationship, for technological and nanomedical applications.

Atomistic simulations of gold surface functionalization for nanoscale biosensors applications

A wide class of biosensors can be built via functionalization of gold surface with proper bio conjugation element capable of interacting with the analyte in solution, and the detection can be performed either optically, mechanically or electrically. Any change in physico-chemical environment or any slight variation in mass localization near the surface of the sensor can cause differences in nature of the transduction mechanism. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection of the analyte. Here, we employ molecular modeling techniques to assist the optimization of a gold-surface biosensor. The gold surface of a quartz-crystal-microbalance sensor is functionalized using polymeric chains of poly(ethylene glycol) (PEG) of 2 KDa molecular weight, which is an inert long chain amphiphilic molecule, supporting biotin molecules (bPEG) as the ligand molecules for streptavidin analyte. The PEG linkers are immobilized onto the gold surface through sulphur chemistry. Four gold surfaces with different PEG linker density and different biotinylation ratio between bPEG and PEG, are investigated by means of state-of-the art atomistic simulations and compared with available experimental data. Results suggest that the amount of biotin molecules accessible for the binding with the protein increases upon increasing the linkers density. At the high density a 1:1 ratio of bPEG/PEG can further improve the accessibility of the biotin ligand due to a strong repulsion between linker chains and different degree of hydrophobicity between bPEG and PEG linkers. The study provides a computaional protocol to model sensors at the level of single molecular interactions, and for optimizing the physical properties of surface conjugated ligand which is crucial to enhance output of the sensor.

Conformation-dependent charge transport through short peptides

We report on charge transport across single short peptides using the Mechanically Controlled Break Junction (MCBJ) method. We record thousands of electron transport events across single-molecule junctions and with an unsupervised machine learning algorithm, we identify several classes of traces with multifarious conductance values that may correspond to different peptide conformations. Data analysis shows that very short peptides, which are more rigid, show conductance plateaus at low conductance values of about 10^-3G₀ and below, with G₀ being the conductance quantum, whereas slightly longer, more flexible peptides also show plateaus at higher values. Fully stretched peptide chains exhibit conductance values that are of the same order as that of alkane chains of similar length. The measurements show that in the case of short peptides, different compositions and molecular lengths offer a wide range of junction conformations. Such information is crucial to understand mechanism(s) of charge transport in and across peptide-based biomolecules.

The membrane axis of Alzheimer's nanomedicine

Alzheimer's disease (AD) is a major neurological disorder impairing its carrier's cognitive function, memory and lifespan. While the development of AD nanomedicine is still nascent, the field is evolving into a new scientific frontier driven by the diverse physicochemical properties and theranostic potential of nanomaterials and nanocomposites. Characteristic to the AD pathology is the deposition of amyloid plaques and tangles of amyloid beta (Aβ) and tau, whose aggregation kinetics may be curbed by nanoparticle inhibitors via sequence-specific targeting or nonspecific interactions with the amyloidogenic proteins. As literature implicates cell membrane as a culprit in AD pathogenesis, here we summarize the membrane axis of AD nanomedicine and present a new rationale that the field development may greatly benefit from harnessing our existing knowledge of Aβ-membrane interaction, nanoparticle-membrane interaction and Aβ-nanoparticle interaction.

Simulating selective binding of a biological template to a nanoscale architecture: a core concept of a clamp-based binding-pocket-favored N-terminal-domain assembly

The biological template and its mutants have vital significance in next generation remediation, electrochemical, photovoltaic, catalytic, sensing and digital memory devices. However, a microscopic model describing the biotemplating process is generally lacking on account of modelling complexity, which has prevented widespread commercial use of biotemplates. Here, we demonstrate M13-biotemplating kinetics in atomic resolution by leveraging large-scale molecular dynamics (MD) simulations. The model reveals the assembly of gold nanoparticles on two experimentally-based M13 phage types using full M13-capsid structural models and with polarizable gold nanoparticles in explicit solvent. Both mechanistic and structural insights into the selective binding affinity of the M13 phage to gold nanoparticles are obtained based on a previously unconsidered clamp-based binding-pocket-favored N-terminal-domain assembly and also on surface-peptide flexibility. These results provide a deeper level of understanding of protein sequence-based affinity and open the route for genetically engineering a wide range of 3D electrodes for high-density low-cost device integration.

A new mechanism for reduced cell adhesion: Adsorption dynamics of collagen on a nanoporous gold surface

Nanostructured materials such as nanoparticles and nanoporous materials strongly affect cell behaviors such as cell viability. Because cellular uptake of nanoporous materials does not occur, mechanisms for the effects of nanoporous materials on cells are different from those of nanoparticles. The effects of nanoporous materials on cells are thought to result from large conformational changes in the extracellular matrix (ECM) induced by the nanoporous materials, although the mechanotransduction and the critical focal adhesion cluster size also have an effect on the cell response. However, we show that the adhesion of mesenchymal stem cells to a gold surface is reduced for nanoporous gold (NPG), despite the conformational changes in collagen induced by NPG being below the detection limits of the experimental analyses. The adsorption dynamics of collagen on NPG are investigated by molecular dynamics simulations to determine the origin of the reduced cell adhesion to NPG. The adsorption energy of collagen on NPG is lower than that on flat gold (FG) despite there being little difference between the global conformation of collagen segments adsorbed on NPG compared with FG. This finding is related to the surface strain of NPG and the limited movement of collagen amino acids owing to interchain hydrogen bonds. The results obtained in this study provide new insight into the interactions between nanostructured materials and the ECM.

Coherent Electron Transport across a 3 nm Bioelectronic Junction Made of Multi-Heme Proteins

Multi-heme cytochromes (MHCs) are fascinating proteins used by bacterial organisms to shuttle electrons within, between, and out of their cells. When placed in solid-state electronic junctions, MHCs support temperature-independent currents over several nanometers that are 3 orders of magnitude higher compared to other redox proteins of similar size. To gain molecular-level insight into their astonishingly high conductivities, we combine experimental photoemission spectroscopy with DFT+Σ current-voltage calculations on a representative Gold-MHC-Gold junction. We find that conduction across the dry, 3 nm long protein occurs via off-resonant coherent tunneling, mediated by a large number of protein valence-band orbitals that are strongly delocalized over heme and protein residues. This picture is profoundly different from the electron hopping mechanism induced electrochemically or photochemically under aqueous conditions. Our results imply that the current output in solid-state junctions can be even further increased in resonance, for example, by applying a gate voltage, thus allowing a quantum jump for next-generation bionanoelectronic devices.

Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

A fundamental problem in thermodynamics is the recovery of macroscopic equilibrated interaction energies from experimentally measured single-molecular interactions. The Jarzynski equality forms a theoretical basis in recovering the free energy difference between two states from exponentially averaged work performed to switch the states. In practice, the exponentially averaged work value is estimated as the mean of finite samples. Numerical simulations have shown that samples having thousands of measurements are not large enough for the mean to converge when the fluctuation of external work is above 4 k_BT, which is easily observable in biomolecular interactions. We report the first example of a statistical gamma work distribution applied to single molecule pulling experiments. The Gibbs free energy of surface adsorption can be accurately evaluated even for a small sample size. The values obtained are comparable to those derived from multi-parametric surface plasmon resonance measurements and molecular dynamics simulations.

Measuring interaction energies from experimentally measured single-molecular interactions is challenging. Here, the authors report a gamma work distribution applied to single molecule pulling events for estimating peptide absorption free energy.

Ten Facets, One Force Field: The GAL19 Force Field for Water-Noble Metal Interfaces

Understanding the structure of the water/metal interfaces plays an important role in many areas ranging from surface chemistry to environmental processes. The size, required phase-space sampling, and the slow diffusion of molecules at the water/metal interfaces motivate the development of accurate force fields. We develop and parametrize GAL19, a novel force field, to describe the interaction of water with two facets (111 and 100) of five metals (Pt, Pd, Au, Ag, Cu). To increase transferability compared to its predecessor GAL17, the water-metal interaction is described as a sum of pairwise terms. The interaction energy has three contributions: (i) physisorption is described via a Tang and Toennies potential, (ii) chemisorption and surface corrugation rely on an attractive Gaussian term, and (iii) the angular dependence is explicitly included as a truncated Fourier series. Thirteen parameters are used for each metal surface and were fitted on 250 water adsorption energies computed at the PBE+dDsC level. The performance of GAL19 was evaluated on a set of more than 600 DFT adsorption energies for each surface, leading to an average root-mean-square deviation of only 1 kcal/mol, correctly reproducing the adsorption trends: strong on Pt and Pd but weaker on Ag, Au, and Cu. This force field was then used to simulate the water/metal interface for all ten surfaces for 1 ns. Structural analyses reveal similar tendencies for all surfaces: a first, dense water layer that is mostly adsorbed on the metal top sites and a second layer up to around 6 Å, which is less structured. On Pt and Pd, the first layer is strongly organized with water lying flat on the surface. The pairwise additive functional form allows one to simulate the water adsorption on alloys, which is demonstrated at the example of Ag/Cu and Au/Pt alloys. The water/Ag-Cu interface is predicted to be disordered with water mostly adsorbed on Cu which should exacerbate the Ag reactivity. On the contrary, incorporating Pt into Au materials leads to a structuring of the water interface. Our promising results make GAL19 an ideal candidate to get representative sampling of complex metal/water interfaces as a first step toward accurate estimation of free energies of reactions in solution at the metal interface.

The Molecular Dynamics Simulation of Peptides on Gold Nanosurfaces

This chapter contributes a short tutorial on the preparation of molecular dynamics (MD) simulations for a peptide in solution at the interface of an uncoated gold nanosurface. Specifically, the step-by-step procedure will give guidance to set up the simulation of a 16 amino acid long antimicrobial peptide on a gold layer using the program Gromacs for MD simulations.

Determination and evaluation of the nonadditivity in wetting of molecularly heterogeneous surfaces

Every folded protein presents an interface with water that is composed of domains of varying hydrophilicity/-phobicity. Many simulation studies have highlighted the nonadditivity in the wetting of such nanostructured surfaces in contrast with the accepted theoretical formula that is additive. We present here an experimental study on surfaces of identical composition but different organization of hydrophobic and hydrophilic domains. We prove that the interfacial energy of such surfaces differs by ∼20% and that a significant difference in the interfacial water H-bonding structure can be measured. As a result, in combination with molecular-dynamics simulations, we propose a model that captures the wetting of molecularly heterogeneous surfaces, showing the importance of local structure (first-nearest neighbors) in determining the wetting properties.

The interface between water and folded proteins is very complex. Proteins have “patchy” solvent-accessible areas composed of domains of varying hydrophobicity. The textbook understanding is that these domains contribute additively to interfacial properties (Cassie’s equation, CE). An ever-growing number of modeling papers question the validity of CE at molecular length scales, but there is no conclusive experiment to support this and no proposed new theoretical framework. Here, we study the wetting of model compounds with patchy surfaces differing solely in patchiness but not in composition. Were CE to be correct, these materials would have had the same solid–liquid work of adhesion (W_SL) and time-averaged structure of interfacial water. We find considerable differences in W_SL, and sum-frequency generation measurements of the interfacial water structure show distinctively different spectral features. Molecular-dynamics simulations of water on patchy surfaces capture the observed behaviors and point toward significant nonadditivity in water density and average orientation. They show that a description of the molecular arrangement on the surface is needed to predict its wetting properties. We propose a predictive model that considers, for every molecule, the contributions of its first-nearest neighbors as a descriptor to determine the wetting properties of the surface. The model is validated by measurements of W_SL in multiple solvents, where large differences are observed for solvents whose effective diameter is smaller than ∼6 Å. The experiments and theoretical model proposed here provide a starting point to develop a comprehensive understanding of complex biological interfaces as well as for the engineering of synthetic ones.

Low-Resolution Models for the Interaction Dynamics of Coated Gold Nanoparticles with β2-microglobulin

A large number of low-resolution models have been proposed in the last decades to reduce the computational cost of molecular dynamics simulations for bio-nano systems, such as those involving the interactions of proteins with functionalized nanoparticles (NPs). For the proteins, “minimalist” models at the one-bead-per residue (Cα-based) level and with implicit solvent are well established. For the gold NPs, widely explored for biotechnological applications, mesoscale (MS) models treating the NP core with a single spheroidal object are commonly proposed. In this representation, the surface details (coating, roughness, etc.) are lost. These, however, and the specificity of the functionalization, have been shown to have fundamental roles for the interaction with proteins. We presented a mixed-resolution coarse-grained (CG) model for gold NPs in which the surface chemistry is reintroduced as superficial smaller beads. We compared molecular dynamics simulations of the amyloid β2-microglobulin represented at the minimalist level interacting with NPs represented with this model or at the MS level. Our finding highlights the importance of describing the surface of the NP at a finer level as the chemical-physical properties of the surface of the NP are crucial to correctly understand the protein-nanoparticle association.