Computational Study of the Forces Driving Aggregation of Ultrasmall Nanoparticles in Biological Fluids

Stealth and Biocompatible Gold Nanoparticles through Surface Coating with a Zwitterionic Derivative of Glutathione

Gold nanoparticles (AuNPs) hold promise in biomedicine, but challenges like aggregation, protein corona formation, and insufficient biocompatibility must be thoroughly addressed before advancing their clinical applications. Designing AuNPs with specific protein corona compositions is challenging, and strategies for corona elimination, such as coating with polyethylene glycol (PEG), have limitations. In this study, we introduce a commercially available zwitterionic derivative of glutathione, glutathione monoethyl ester (GSHzwt), for the surface coating of colloidal AuNPs. Particles coated with GSHzwt were investigated alongside four other AuNPs coated with various ligands, including citrate ions, tiopronin, glutathione, cysteine, and PEG. We then undertook a head-to-head comparison of these AuNPs to assess their behavior in biological fluid. GSHzwt-coated AuNPs exhibited exceptional resistance to aggregation and protein adsorption. The particles could also be readily functionalized with biotin and interact with streptavidin receptors in human plasma. Additionally, they exhibited significant blood compatibility and noncytotoxicity. In conclusion, GSHzwt provides a practical and easy method for the surface passivation of AuNPs, creating "stealth" particles for potential clinical applications.

Determining depletion interactions by contracting forces

Depletion forces are fundamental for determining the phase behavior of a vast number of materials and colloidal dispersions, and have been used for the manipulation of in- and out-of-equilibrium thermodynamic states. The entropic nature of depletion forces is well understood; however, most theoretical approaches, and also molecular simulations, work quantitatively at moderate size ratios in very diluted systems, since large size asymmetries and high particle concentrations are difficult to deal with. The existing approaches for integrating out the degrees of freedom of the depletant species may fail under these extreme physical conditions. Thus, the main goal of this contribution is to introduce a general physical formulation for obtaining the depletion forces even in those cases where the concentration of all species is relevant. We show that the contraction of the bare forces uniquely determines depletion interactions. Our formulation is tested by studying depletion forces in binary and ternary colloidal mixtures. We report here results for dense systems, with total packing fractions of 45\% and 55\%. Our results open up the possibility of finding an efficient route to determine effective interactions at finite concentration, even at non-equilibrium thermodynamic conditions.

Biomolecular interactions of ultrasmall metallic nanoparticles and nanoclusters

The use of nanoparticles (NPs) in biomedicine has made a gradual transition from proof-of-concept to clinical applications, with several NP types meeting regulatory approval or undergoing clinical trials. A new type of metallic nanostructures called ultrasmall nanoparticles (usNPs) and nanoclusters (NCs), while retaining essential properties of the larger (classical) NPs, have features common to bioactive proteins. This combination expands the potential use of usNPs and NCs to areas of diagnosis and therapy traditionally reserved for small-molecule medicine. Their distinctive physicochemical properties can lead to unique in vivo behaviors, including improved renal clearance and tumor distribution. Both the beneficial and potentially deleterious outcomes (cytotoxicity, inflammation) can, in principle, be controlled through a judicious choice of the nanocore shape and size, as well as the chemical ligands attached to the surface. At present, the ability to control the behavior of usNPs is limited, partly because advances are still needed in nanoengineering and chemical synthesis to manufacture and characterize ultrasmall nanostructures and partly because our understanding of their interactions in biological environments is incomplete. This review addresses the second limitation. We review experimental and computational methods currently available to understand molecular mechanisms, with particular attention to usNP-protein complexation, and highlight areas where further progress is needed. We discuss approaches that we find most promising to provide relevant molecular-level insight for designing usNPs with specific behaviors and pave the way to translational applications.

Exploration and insights into the cellular internalization and intracellular fate of amphiphilic polymeric nanocarriers

The beneficial or deleterious effects of nanomedicines emerge from their complex interactions with intracellular pathways and their subcellular fate. Moreover, the dynamic nature of plasma membrane accounts for the movement of these nanocarriers within the cell towards different organelles thereby not only influencing their pharmacokinetic and pharmacodynamic properties but also bioavailability, therapeutic efficacy and toxicity. Therefore, an in-depth understanding of underlying parameters controlling nanocarrier endocytosis and intracellular fate is essential. In order to direct nanoparticles towards specific sub-cellular organelles the physicochemical attributes of nanocarriers can be manipulated. These include particle size, shape and surface charge/chemistry. Restricting the particle size of nanocarriers below 200 nm contributes to internalization via clathrin and caveolae mediated pathways. Similarly, a moderate negative surface potential confers endolysosomal escape and targeting towards mitochondria, endoplasmic reticulum (ER) and Golgi. This review aims to provide an insight into these physicochemical attributes of nanocarriers fabricated using amphiphilic graft copolymers affecting cellular internalization. Fundamental principles understood from experimental studies have been extrapolated to draw a general conclusion for the designing of optimized nanoparticulate drug delivery systems and enhanced intracellular uptake via specific endocytic pathway.

Artificial neural networks for the inverse design of nanoparticles with preferential nano-bio behaviors

Safe and efficient use of ultrasmall nanoparticles (NPs) in biomedicine requires numerous independent conditions to be met, including colloidal stability, selectivity for proteins and membranes, binding specificity, and low affinity for plasma proteins. The ability of a NP to satisfy one or more of these requirements depends on its physicochemical characteristics, such as size, shape, and surface chemistry. Multiscale and pattern recognition techniques are here integrated to guide the design of NPs with preferential nano-bio behaviors. Data systematically collected from simulations (or experiments, if available) are first used to train one or more artificial neural networks, each optimized for a specific kind of nano-bio interaction; the trained networks are then interconnected in suitable arrays to obtain the NP core morphology and layer composition that best satisfy all the nano-bio interactions underlying more complex behaviors. This reverse engineering approach is illustrated in the case of NP-membrane interactions, using binding modes and affinities and early stage membrane penetrations as training data. Adaptations for designing NPs with preferential nano-protein interactions and for optimizing solution conditions in the test tube are discussed.

Ultrasmall Gold Nanoparticles Coated with Zwitterionic Glutathione Monoethyl Ester: A Model Platform for the Incorporation of Functional Peptides

Ultrasmall gold nanoparticles (AuNPs) are an emerging class of nanomaterials exhibiting distinctive physicochemical, molecular, and in vivo properties. Recently, we showed that ultrasmall AuNPs encompassing a zwitterionic glutathione monoethyl ester surface coating (AuGSHzwt) were highly resistant to aggregation and serum protein interactions. Herein, we performed a new set of biointeraction studies to gain a more fundamental understanding into the behavior of both pristine and peptide-functionalized AuGSHzwt in complex media. Using the model Strep-tag peptide (WSHPQFEK) as an integrated functional group, we established that AuGSHzwt could be conjugated with increasing numbers of Strep-tags by simple ligand exchange, which provides a generic approach for AuGSHzwt functionalization. It was found that the strep-tagged AuGSHzwt particles were highly resistant to nonspecific protein interactions and retained their targeting capability in biological fluid, displaying efficient binding to Streptactin receptors in nearly undiluted serum. However, AuGSHzwt functionalized with multiple Strep-tags displayed somewhat lower resistance to protein interactions and lower levels of binding to Streptactin than monofunctionalized AuGSHzwt under given conditions. These results underscore the need for optimizing ligand density onto the surface of ultrasmall AuNPs for improved performance. Collectively, our findings support ultrasmall AuGSHzwt as an attractive platform for engineering functional, protein-mimetic nanostructures capable of specific protein recognition within the complex biological milieu.

Strong dependence of the nano-bio interactions on core morphology and layer composition of ultrasmall nanostructures

The interactions between nanoparticles (NPs) and proteins, cells, and tissues, broadly known as nano-bio interactions, depend on the NP size and shape and on the characteristics of the NP coating layer, such as density, thickness, and chemical makeup. The dependence of nano-membrane interactions on the design parameters of ultrasmall nanostructures is studied by computer simulations. Considered here are spheres, plates, rings, rods, tubes, and helices made up of either bare magnetite or passivated gold, interacting with charged or zwitterionic membranes. The analysis reveals a strong dependence on shape, size, and layer composition of various quantities that characterize the nano-bio behavior, including binding modes and affinities. This sensitivity can be exploited to design nanostructures that bind preferentially to membranes or that stabilize or disrupt membrane structural integrity. The method used here is general and not limited to the ultrasmall regime, so it can be adopted to study other nano-bio interactions systematically. The implications for the distribution of NPs in cells and tissues (biodistribution) and for passive and active transmembrane transport are discussed, both important processes in biomedicine.

Self-adaptive multiscaling algorithm for efficient simulations of many-protein systems in crowded conditions

A method is described for the efficient simulation of multiprotein systems in crowded environments. It is based on an adaptive, reversible structural coarsening algorithm that preserves relevant physical features of the proteins across scales. Water is treated implicitly whereas all the other components of the aqueous solution, such as ions, cosolutes, or osmolytes, are treated in atomic detail. The focus is on the analytical adaptation of the solvent model to different levels of molecular resolutions, which allows continuous, on-the-fly transitions between scales. This permits the analytical calculation of forces during dynamics and preserves detailed balance in Monte Carlo simulations. A major computational speedup can be achieved in systems containing hundreds of proteins without cutting off the long-range interactions. The method can be combined with a self-adaptive configurational-bias sampling technique described previously, designed to detect strong, weak, or ultra-weak protein associations and shown to improve sampling efficiency and convergence. The implementation aims to simulate early stages of multimeric complexation, aggregation, or self-assembly. The method can be adopted as the basis for a more general algorithm to identify vertices, edges, and hubs in protein interaction networks or to predict critical steps in signal transduction pathways.

Macromolecular crowding for materials-directed controlled self-assembly

Macromolecular crowding refers to intracellular environments where various macromolecules, including proteins and nucleic acids, are present at high total concentrations. Its influence on biological processes has been investigated using a highly concentrated in vitro solution of water-soluble polymers as a model. Studies have revealed significant effects of macromolecular crowding on the thermodynamic equilibria and dynamics of biomolecular self-assembly in vivo. Recently, macromolecular crowding has attracted materials scientists, especially those in bio-related areas, as a tool to control molecular/colloidal self-assembly. Macromolecular crowding has been exploited to control the structure of supramolecular materials, assemble nanomaterials, and improve the performance of polymeric materials. Furthermore, nanostructured materials have been shown to be an interesting alternative to water-soluble polymers for creating crowded environments for controlled self-assembly. In this review article, we summarize recent progress in research on macromolecular crowding for controlled self-assembly in bio-related materials chemistry.

Binding kinetics of ultrasmall gold nanoparticles with proteins

Synthetic ultrasmall nanoparticles (NPs) can be designed to interact with biologically active proteins in a controlled manner. However, the rational design of NPs requires a clear understanding of their interactions with proteins and the precise molecular mechanisms that lead to association/dissociation in biological media. Although much effort has been devoted to the study of the kinetics mechanism of protein corona formation on large NPs, the nature of NP-protein interactions in the ultrasmall regime is radically different and poorly understood. Using a combination of experimental and computational approaches, we studied the interactions of a model protein, CrataBL, with ultrasmall gold NPs passivated with p-mercaptobenzoic acid (AuMBA) and glutathione (AuGSH). We have identified this system as an ideal in vitro platform to understand the dependence of binding affinity and kinetics on NP surface chemistry. We found that the structural and chemical complexity of the passivating NP layer leads to quite different association kinetics, from slow and reaction-limited (AuGSH) to fast and diffusion-limited (AuMBA). We also found that the otherwise weak and slow AuGSH-protein interactions measured in buffer solution are enhanced in macromolecular crowded solutions. These findings advance our mechanistic understanding of biomimetic NP-protein interactions in the ultrasmall regime and have implications for the design and use of NPs in the crowded conditions common to all biological media.

Determination of the local density of polydisperse nanoparticle assemblies

Quantitative characterization of the average structure of dense nanoparticle assemblies and aggregates is a common problem in nanoscience. Small-angle scattering is a suitable technique, but it is usually limited to not too big assemblies due to the limited experimental range, low concentrations to avoid interactions, and monodispersity to keep calculations tractable. In the present paper, a straightforward analysis of the generally available scattered intensity - even for large assemblies, at high concentrations - is detailed, providing information on the local volume fraction of polydisperse particles with hard sphere interactions. It is based on the identical local structure of infinite homogeneous nanoparticle assemblies and their subsets forming finite-sized clusters. This approach is extended to polydispersity, using Monte-Carlo simulations of hard and moderately sticky hard spheres. As a result, a simple relationship between the observed structure factor minimum - termed the correlation hole - and the average local volume fraction κ on the scale of neighboring particles is proposed and validated through independent aggregate simulations. This relationship shall be useful as an efficient tool for the structural analysis of arbitrarily aggregated colloidal systems.