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.

Role of Ionic Strength in the Formation of Stable Supramolecular Nanoparticle-Protein Conjugates for Biosensing.

Monolayer-protected gold nanoparticles (AuNPs) exhibit distinct physical and chemical properties depending on the nature of the ligand chemistry. A commonly employed NP monolayer comprises hydrophobic molecules linked to a shell of PEG and terminated with functional end group, which can be charged or neutral. Different layers of the ligand shell can also interact in different manners with proteins, expanding the range of possible applications of these inorganic nanoparticles. AuNP-fluorescent Green Fluorescent Protein (GFP) conjugates are gaining increasing attention in sensing applications. Experimentally, their stability is observed to be maintained at low ionic strength conditions, but not at physiologically relevant conditions of higher ionic strength, limiting their applications in the field of biosensors. While a significant amount of fundamental work has been done to quantify electrostatic interactions of colloidal nanoparticle at the nanoscale, a theoretical description of the ion distribution around AuNPs still remains relatively unexplored. We perform extensive atomistic simulations of two oppositely charged monolayer-protected AuNPs interacting with fluorescent supercharged GFPs co-engineered to have complementary charges. These simulations were run at different ionic strengths to disclose the role of the ionic environment on AuNP-GFP binding. The results highlight the capability of both AuNPs to intercalate ions and water molecules within the gold-sulfur inner shell and the different tendency of ligands to bend inward allowing the protein to bind not only with the terminal ligands but also the hydrophobic alkyl chains. Different binding stability is observed in the two investigated cases as a function of the ligand chemistry.

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.

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.

Low-Resolution Models for the Interaction Dynamics of Coated Gold Nanoparticles with ß2-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 ß2-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.

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.

Aggregation behavior of nanoparticles: Revisiting the phase diagram of colloids.

Surface functionalization of metal nanoparticles (NPs), e.g., using peptides and proteins, has recently attracted a considerable attention in the field of design of therapeutics and diagnostics. The possibility of diverse functionalization allows them to selectively interact with proteins, while the metal core ensures solubility, making them tunable therapeutic agents against diseases due to mis-folding or aggregation. On the other hand, their action is limited by possible self-aggregation, which could be, however, prevented based on the full understanding of their phase diagram as a function of the environmental variables (temperature, ionic strength of the solution, concentration) and intrinsic characteristics (size, charge, amount, and type of functional groups). A common modeling strategy to study the phase behavior is to represent the NPs as spheres interacting via effective potentials implicitly accounting for the solvation effects. Their size put the NPs into the class of colloids, albeit with particularly complex interactions including both attractive and repulsive features, and a consequently complex phase diagram. In this work, we review the studies exploring the phases of these systems starting from those with only attractive or repulsive interactions, displaying a simpler disperse-clustered-aggregated transitions. The phase diagram is here interpreted focusing on the universal aspects, i.e., those dependent on the general feature of the potentials, and available data are organized in a parametric phase diagram. We then consider the potentials with competing attractive short range well and average-long-range repulsive tail, better representing the NPs. Through the proper combination of the attractive only and repulsive only potentials, we are able to interpret the appearance of novel phases, characterized by aggregates with different structural characteristics. We identify the essential parameters that stabilize the disperse phase potentially useful to optimize NP therapeutic activity and indicate how to tune the phase behavior by changing environmental conditions or the NP chemical-physical properties.

Combining enhanced sampling and deep learning dimensionality reduction for the study of the heat shock protein B8 and its pathological mutant K141E.

The biological functions of proteins closely depend on their conformational dynamics. This aspect is especially relevant for intrinsically disordered proteins (IDP) for which structural ensembles often offer more useful representations than individual conformations. Here we employ extensive enhanced sampling temperature replica-exchange atomistic simulations (TREMD) and deep learning dimensionality reduction to study the conformational ensembles of the human heat shock protein B8 and its pathological mutant K141E, for which no experimental 3D structures are available. First, we combined homology modelling with TREMD to generate high-dimensional data sets of 3D structures. Then, we employed a recently developed machine learning based post-processing algorithm, EncoderMap, to project the large conformational data sets into meaningful two-dimensional maps that helped us interpret the data and extract the most significant conformations adopted by both proteins during TREMD. These studies provide the first 3D structural characterization of HSPB8 and reveal the effects of the pathogenic K141E mutation on its conformational ensembles. In particular, this missense mutation appears to increase the compactness of the protein and its structural variability, at the same time rearranging the hydrophobic patches exposed on the protein surface. These results offer the possibility of rationalizing the pathogenic effects of the K141E mutation in terms of conformational changes.

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.

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.

Combined effects of metal complexation and size expansion in the electronic structure of DNA base pairs.

Novel DNA derivatives have been recently investigated in the pursuit of modified DNA duplexes to tune the electronic structure of DNA-based assemblies for nanotechnology applications. Size-expanded DNAs (e.g., xDNA) and metalated DNAs (M-DNA) may enhance stacking interactions and induce metallic conductivity, respectively. Here we explore possible ways of tailoring the DNA electronic structure by combining the aromatic size expansion with the metal-doping. We select the salient structures from our recent study on natural DNA pairs complexed with transition metal ions and consider the equivalent model configurations for xDNA pairs. We present the results of density functional theory electronic structure calculations of the metalated expanded base-pairs with various localized basis sets and exchange-correlation functionals. Implicit solvent and coordination water molecules are also included. Our results indicate that the effect of base expansion is largest in Ag-xGC complexes, while Cu-xGC complexes are the most promising candidates for nanowires with enhanced electron transfer and also for on-purpose modification of the DNA double-helix for signal detection.

Self-organization, optical, and electrical properties of alpha-quinquethiophene-dinucleotide conjugates.

The synthesis and properties of (5')TA(3')-t5 (8a) and (5')CG(3')-t5 (8b) conjugates, in which the self-complementary dinucleotides TA and CG are covalently bound to the central ring of alpha-quinquethiophene (t5), are described. According to molecular mechanics calculations, the preferred conformation of both 8a and 8b is that with the dinucleotide folded over the planar t5 backbone, with the nucleobases facing t5 at stacking distance. The calculations show that the aggregation process of 8a and 8b is driven by a mix of nucleobase-thiophene interactions, hydrogen bonding between nucleobases (non Watson-Crick (W&C) in TA, and W&C in CG), van der Waals, and electrostatic interactions. While 8b is scarcely soluble in any solvents, 8a is soluble in water, indicating that the aggregates of the former are more stable than those of the latter. Microfluidic-induced self-assembly studies of 8a showed the formation of lamellar, spherulitic, and dendritic supramolecular structures, depending on the concentration and solvent evaporation time. The self-assembled structures displayed micrometer dimensions in the xy plane of the substrate and nanometer dimensions in the z direction. Spatially resolved confocal microscopy and spectroscopy showed that the aggregates were characterized by intense fluorescence emission. Cast films of 8a from water solutions showed chirality transfer from the dinucleotide to t5. The hole mobility of the cast films of 8a was estimated using a two-electrode device under high vacuum and found to be up to two orders of magnitude greater than those previously measured for dinucleotide-quarterthiophene conjugates under the same experimental conditions.

Electronic properties of metal-modified DNA base pairs.

The electronic properties of several metal-modified Watson-Crick guanine-cytosine base pairs are investigated by means of first-principle density functional theory calculations. Focus is placed on a new structure recently proposed as a plausible model for building an antiparallel duplex with Zn-guanine-cytosine pairs, but we also inspect several other conformations and the incorporation of Ag and Cu ions. We analyze the effects induced by the incorporation of one metal cation per base pair by comparing the structures and the electronic properties of the metalated pairs to those of the natural guanine-cytosine pair, particularly for what concerns the modifications of energy levels and charge density distributions of the frontier orbitals. Our results reveal the establishment of covalent bonding between the metal cation and the nucleobases, identified in the presence of hybrid metal-guanine and metal-cytosine orbitals. Attachment of the cation can occur either at the N1 or the N7 site of guanine and is compatible with altering or not altering the H-bond pattern of the natural pair. Cu(II) strongly contributes to the hybridization of the orbitals around the band gap, whereas Ag(I) and Zn(II) give hybrid states farther from the band gap. Most metalated pairs have smaller band gaps than the natural guanine-cytosine pair. The band gap shrinking along with the metal-base coupling suggests interesting consequences for electron transfer through DNA double helices.

Citrate stabilized gold nanoparticles interfere with amyloid fibril formation: D76N and ΔN6 ß2-microglobulin variants.

Protein aggregation including the formation of dimers and multimers in solution, underlies an array of human diseases such as systemic amyloidosis which is a fatal disease caused by misfolding of native globular proteins damaging the structure and function of affected organs. Different kind of interactors can interfere with the formation of protein dimers and multimers in solution. A very special class of interactors are nanoparticles thanks to the extremely efficient extension of their interaction surface. In particular citrate-coated gold nanoparticles (cit-AuNPs) were recently investigated with amyloidogenic protein ß2-microglobulin (ß2m). Here we present the computational studies on two challenging models known for their enhanced amyloidogenic propensity, namely ΔN6 and D76N ß2m naturally occurring variants, and disclose the role of cit-AuNPs on their fibrillogenesis. The proposed interaction mechanism lies in the interference of the cit-AuNPs with the protein dimers at the early stages of aggregation, that induces dimer disassembling. As a consequence, natural fibril formation can be inhibited. Relying on the comparison between atomistic simulations at multiple levels (enhanced sampling molecular dynamics and Brownian dynamics) and protein structural characterisation by NMR, we demonstrate that the cit-AuNPs interactors are able to inhibit protein dimer assembling. As a consequence, the natural fibril formation is also inhibited, as found in experiment.

Citrate-stabilized gold nanoparticles hinder fibrillogenesis of a pathological variant of ß2-microglobulin.

Nanoparticles have repeatedly been shown to enhance fibril formation when assayed with amyloidogenic proteins. Recently, however, evidence casting some doubt about the generality of this conclusion started to emerge. Therefore, to investigate further the influence of nanoparticles on the fibrillation process, we used a naturally occurring variant of the paradigmatic amyloidogenic protein ß2-microglobulin (ß2m), namely D76N ß2m where asparagine replaces aspartate at position 76. This variant is responsible for aggressive systemic amyloidosis. After characterizing the interaction of the variant with citrate-stabilized gold nanoparticles (Cit-AuNPs) by NMR and modeling, we analyzed the fibril formation by three different methods: thioflavin T fluorescence, native agarose gel electrophoresis and transmission electron microscopy. The NMR evidence indicated a fast-exchange interaction involving preferentially specific regions of the protein that proved, by subsequent modeling, to be consistent with a dimeric adduct interacting with Cit-AuNPs. The fibril detection assays showed that AuNPs are able to hamper D76N ß2m fibrillogenesis through an effective interaction that competes with protofibril formation or recruitment. These findings open promising perspectives for the optimization of the nanoparticle surface to design tunable interactions with proteins.

Lithium intercalation of phenyl-capped aniline dimers: a study by photoelectron spectroscopy and quantum chemical calculations.

Structural and electronic properties of pristine and lithium-intercalated, phenyl-capped aniline dimers as a model for the lithium-polyaniline system have been studied by photoelectron spectroscopy and quantum chemical calculations. It was found that the electronic structure of reduced and oxidized forms of oligoanilines is only weakly affected by isomerism. Upon intercalation, charge transfer from the Li-atoms is remarkable and highly localized at N-atomic sites, where configurations are energetically favored in which both N atoms of the dimers are bound to Li atoms. Conversion of nitrogen sites is different for the two forms of aniline dimers and incomplete up to high intercalation levels, indicating a pronounced role of solid-state effects in the formation of such compounds.

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations.

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of ß2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of ß2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Probing the influence of citrate-capped gold nanoparticles on an amyloidogenic protein.

Nanoparticles (NPs) are known to exhibit distinct physical and chemical properties compared with the same materials in bulk form. NPs have been repeatedly reported to interact with proteins, and this interaction can be exploited to affect processes undergone by proteins, such as fibrillogenesis. Fibrillation is common to many proteins, and in living organisms, it causes tissue-specific or systemic amyloid diseases. The nature of NPs and their surface chemistry is crucial in assessing their affinity for proteins and their effects on them. Here we present the first detailed structural characterization and molecular mechanics model of the interaction between a fibrillogenic protein, ß2-microglobulin, and a NP, 5 nm hydrophilic citrate-capped gold nanoparticles. NMR measurements and simulations at multiple levels (enhanced sampling molecular dynamics, Brownian dynamics, and Poisson-Boltzmann electrostatics) explain the origin of the observed protein perturbations mostly localized at the amino-terminal region. Experiments show that the protein-NP interaction is weak in the physiological-like, conditions and do not induce protein fibrillation. Simulations reproduce these findings and reveal instead the role of the citrate in destabilizing the lower pH protonated form of ß2-microglobulin. The results offer possible strategies for controlling the desired effect of NPs on the conformational changes of the proteins, which have significant roles in the fibrillation process.

Can small hydrophobic gold nanoparticles inhibit ß2-microglobulin fibrillation?

Inorganic nanoparticles stabilized by a shell of organic ligands can enhance or suppress the natural propensity of proteins to form fibrils. Functionalization facilitates targeted delivery of the nanoparticles to various cell types, bioimaging, drug delivery and other therapeutic and diagnostic applications. In this study, we provide a computational model of the effect of a prototypical thiol-protected gold nanoparticle, Au25L18(-) (L = S(CH2)2Ph) on the ß2-microglobulin natural fibrillation propensity. To reveal the molecular basis of the protein-nanoparticle association process, we performed various simulations at multiple levels (Classical Molecular Dynamics and Brownian Dynamics) that cover multiple length- and timescales. The results provide a model of the ensemble of structures constituting the protein-gold nanoparticle complexes, and insights into the driving forces for the binding of ß2-microglobulin to hydrophobic small size gold nanoparticles. We have found that the small nanoparticles can bind the protein to form persistent complexes. This binding of nanoparticles is able to block the active sites of domains from binding to another protein, thus leading to potential inhibition of the fibrillation activity. A comparison with the binding patches identified for the interaction of the protein with a known inhibitor of fibrillation, supports our conclusion.