Optimizing the selective recognition of protein isoforms through tuning of nanoparticle hydrophobicity

Predicting the Physicochemical Properties and Biological Activities of Monolayer-Protected Gold Nanoparticles Using Simulation-Derived Descriptors

Gold nanoparticles are versatile materials for biological applications because their properties can be modulated by assembling ligands on their surface to form monolayers. However, the physicochemical properties and behaviors of monolayer-protected nanoparticles in biological environments are difficult to anticipate because they emerge from the interplay of ligand-ligand and ligand-solvent interactions that cannot be readily inferred from ligand chemical structure alone. In this work, we demonstrate that quantitative nanostructure-activity relationship (QNAR) models can employ descriptors calculated from molecular dynamics simulations to predict nanoparticle properties and cellular uptake. We performed atomistic molecular dynamics simulations of 154 monolayer-protected gold nanoparticles and calculated a small library of simulation-derived descriptors that capture nanoparticle structural and chemical properties in aqueous solution. We then parametrized QNAR models using interpretable regression algorithms to predict experimental measurements of nanoparticle octanol-water partition coefficients, zeta potentials, and cellular uptake obtained from a curated database. These models reveal that simulation-derived descriptors can accurately predict experimental trends and provide physical insight into what descriptors are most important for obtaining desired nanoparticle properties or behaviors in biological environments. Finally, we demonstrate model generalizability by predicting cell uptake trends for 12 nanoparticles not included in the original data set. These results demonstrate that QNAR models parametrized with simulation-derived descriptors are accurate, generalizable computational tools that could be used to guide the design of monolayer-protected gold nanoparticles for biological applications without laborious trial-and-error experimentation.

Identifying nonadditive contributions to the hydrophobicity of chemically heterogeneous surfaces via dual-loop active learning

Hydrophobic interactions drive numerous biological and synthetic processes. The materials used in these processes often possess chemically heterogeneous surfaces that are characterized by diverse chemical groups positioned in close proximity at the nanoscale; examples include functionalized nanomaterials and biomolecules, such as proteins and peptides. Nonadditive contributions to the hydrophobicity of such surfaces depend on the chemical identities and spatial patterns of polar and nonpolar groups in ways that remain poorly understood. Here, we develop a dual-loop active learning framework that combines a fast reduced-accuracy method (a convolutional neural network) with a slow higher-accuracy method (molecular dynamics simulations with enhanced sampling) to efficiently predict the hydration free energy, a thermodynamic descriptor of hydrophobicity, for nearly 200 000 chemically heterogeneous self-assembled monolayers (SAMs). Analysis of this dataset reveals that SAMs with distinct polar groups exhibit substantial variations in hydrophobicity as a function of their composition and patterning, but the clustering of nonpolar groups is a common signature of highly hydrophobic patterns. Further molecular dynamics analysis relates such clustering to the perturbation of interfacial water structure. These results provide new insight into the influence of chemical heterogeneity on hydrophobicity via quantitative analysis of a large set of surfaces, enabled by the active learning approach.

Probing Multiscale Factors Affecting the Reactivity of Nanoparticle-Bound Molecules

The structures and physicochemical properties of surface-stabilizing molecules play a critical role in defining the properties, interactions, and functionality of hybrid nanomaterials such as monolayer-stabilized nanoparticles. Concurrently, the distinct surface-bound interfacial environment imposes very specific conditions on molecular reactivity and behavior in this setting. Our ability to probe hybrid nanoscale systems experimentally remains limited, yet understanding the consequences of surface confinement on molecular reactivity is crucial for enabling predictive nanoparticle synthon approaches for postsynthesis engineering of nanoparticle surface chemistry and construction of devices and materials from nanoparticle components. Here, we have undertaken an integrated experimental and computational study of the reaction kinetics for nanoparticle-bound hydrazones, which provide a prototypical platform for understanding chemical reactivity in a nanoconfined setting. Systematic variation of just one molecular-scale structural parameter-the distance between reactive site and nanoparticle surface-showed that the surface-bound reactivity is influenced by multiscale effects. Nanoparticle-bound reactions were tracked in situ using ¹⁹F NMR spectroscopy, allowing direct comparison to the reactions of analogous substrates in bulk solution. The surface-confined reactions proceed more slowly than their solution-phase counterparts, and kinetic inhibition becomes more significant for reactive sites positioned closer to the nanoparticle surface. Molecular dynamics simulations allowed us to identify distinct supramolecular architectures and unexpected dynamic features of the surface-bound molecules that underpin the experimentally observed trends in reactivity. This study allows us to draw general conclusions regarding interlinked structural and dynamical features across several length scales that influence interfacial reactivity in monolayer-confined environments.

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.

The Interplay of Ligand Properties and Core Size Dictates the Hydrophobicity of Monolayer-Protected Gold Nanoparticles

The hydrophobicity of monolayer-protected gold nanoparticles is a crucial design parameter that influences self-assembly, preferential binding to proteins and membranes, and other nano-bio interactions. Predicting the effects of monolayer components on nanoparticle hydrophobicity is challenging due to the nonadditive, cooperative perturbations to interfacial water structure that dictate hydrophobicity at the nanoscale. In this work, we quantify nanoparticle hydrophobicity by using atomistic molecular dynamics simulations to calculate local hydration free energies at the nanoparticle-water interface. The simulations reveal that the hydrophobicity of large gold nanoparticles is determined primarily by ligand end group chemistry, as expected. However, for small gold nanoparticles, long alkanethiol ligands interact to form anisotropic bundles that lead to substantial spatial variations in hydrophobicity even for homogeneous monolayer compositions. We further show that nanoparticle hydrophobicity is modulated by changing the ligand structure, ligand chemistry, and gold core size, emphasizing that single-ligand properties alone are insufficient to characterize hydrophobicity. Finally, we illustrate that hydration free energy measurements correlate with the preferential binding of propane as a representative hydrophobic probe molecule. Together, these results show that both physical and chemical properties influence the hydrophobicity of small nanoparticles and must be considered together when predicting gold nanoparticle interactions with biomolecules.

Ratiometric Nanoparticle Array-Based Near-Infrared Fluorescent Probes for Quantitative Protein Sensing

Quantitative detection of protein biomarkers is crucial to medical diagnosis. Fluorescent probes have been frequently used for protein detection, but they suffered from various weaknesses such as lack of versatility. In particular, most of the reported probes were not capable of simultaneous qualitative and quantitative detection for various proteins. In this paper, we developed novel nanoparticle array-based near-infrared (NIR) ratiometric probes for potent protein analysis, in which the specific protein was able to be distinguished and quantitated within a group of 11 common proteins. The activity of β-galactosidases (β-gal) was temporarily inhibited by the adsorption to magnetic nanoparticles and restored to certain content by replacement with detected proteins, leading to distinctive readout of the enzyme-activatable NIR probe (DCM-β-gal). The readout of the sensor array against 11 proteins, as verified by isothermal titration calorimetry, was processed and transformed into canonical factors with the help of linear discrimination analysis. Moreover, the ratiometric signals of DCM-β-gal were translated to quantitatively detect proteins within the concentration range of 0-100 μg/mL. Based on clear differentiation within both two-dimensional and three-dimensional plots, different proteins could be detected with 100% accuracy with their concentration simultaneously determined, which endowed the sensing system with great potential in clinical diagnosis.

Protein⁻Polyelectrolyte Interaction: Thermodynamic Analysis Based on the Titration Method †

This review discussed the mechanisms including theories and binding stages concerning the protein⁻polyelectrolyte (PE) interaction, as well as the applications for both complexation and coacervation states of protein⁻PE pairs. In particular, this review focused on the applications of titration techniques, that is, turbidimetric titration and isothermal titration calorimetry (ITC), in understanding the protein⁻PE binding process. To be specific, by providing thermodynamic information such as pHc, pHφ, binding constant, entropy, and enthalpy change, titration techniques could shed light on the binding affinity, binding stoichiometry, and driving force of the protein⁻PE interaction, which significantly guide the applications by utilization of these interactions. Recent reports concerning interactions between proteins and different types of polyelectrolytes, that is, linear polyelectrolytes and polyelectrolyte modified nanoparticles, are summarized with their binding differences systematically discussed and compared based on the two major titration techniques. We believe this short review could provide valuable insight in the understanding of the structure⁻property relationship and the design of applied biomedical PE-based systems with optimal performance.

Pullulan-Based Nanoparticle-HSA Complex Formation and Drug Release Influenced by Surface Charge

The nanomaterial composition of nanoparticles and their protein adsorption in the blood is of great significance in the design of drug-loaded nanoparticles. To explore the interaction between the different surface components of nanoparticles (NPs) and protein, we synthesized three kinds of pullulan NP polymers: cholesteric hydrophobically (CH) modified pullulan (CHP), CH-modified animated pullulan (CHAP), and CH-modified carboxylated pullulan (CHSP). Pullulan NPs were prepared by the dialysis method. Dynamic light scattering was used to determine the charge and size of the three NPs. The size of NPs was altered by the number of charge groups when polymers contain the same degree of cholesterol substitution. The zeta potentials were + 12.9, - 15.4, and - 0.698 mV for CHAP, CHSP, and CHP, respectively, and the dimensions were 116.9, 156.9, and 73.1 nm, respectively. Isothermal titration calorimetry was used to determine the thermodynamic changes of NPs with different surface charge, and the effect of human serum albumin (HSA) on the titration was investigated. The changes of enthalpy and entropy demonstrated an interaction between NPs and HSA; the binding constant (K_b) for CHSP, CHP, and CHAP was 1.41, 27.7, and 412 × 10⁴ M^-1, respectively, with the positive charge for CHAP-HSA, uncharged for CHP-HSA, and negative charge for CHSP-HSA complex. Fluorescence and circular dichroism spectroscopy were used to determine the protein structure change after the complexation between NPs and HSA. The NP and HSA complexation is a complicated process composed of protein α-helical content reduction and the peptide chain extension; CHP NPs had the largest reduction in HSA α-helical content. The drug release rates of all compounds of NP and HSA were significantly lower than those of free drug and drug-loaded NPs after 48 h. The highest and lowest rates were observed in CHSP-HSA and CHP-HSA, respectively. The drug release was significantly influenced by the adsorption of HSA on NPs, and the size and surface charge of NPs played an important role in this process.

Ionic Strength-Responsive Binding between Nanoparticles and Proteins

Electrostatic interaction is a strong, dominant nonspecific interaction which was extensively studied in protein-nanoparticle (NP) interactions [ Lounis , F. M. ; J. Phys. Chem. B 2017 , 121 , 2684 - 2694 ; Tavares , G. M. ; Langmuir 2015 , 31 , 12481 - 12488 ; Antonov , M. ; Biomacromolecules 2010 , 11 , 51 - 59 ], whereas the role of hydrophobic interaction arising from the abundant hydrophobic residues of globule proteins upon protein-NP binding between the proteins and charged nanoparticles has rarely been studied. In this work, a series of positively charged magnetic nanoparticles (MNPs) were prepared via atom transfer radical polymerization and surface hydrophobicity differentiation was achieved through postpolymerization quaternization by different halohydrocarbons. The ionic strength- and hydrophobicity-responsive binding of these MNPs toward β-lactoglobulin (BLG) was studied by both qualitative and quantitative methods including turbidimetric titration, dynamic light scattering, and isothermal titration calorimetry. Judged from the critical binding pH and binding constant for MNP-BLG complexation, the dependence of binding affinity on surface hydrophobicity exhibited an interesting shift with increasing ionic strength, which means that the MNPs with higher surface hydrophobicity exhibits weaker binding affinity at lower ionic strength but stronger affinity at higher ionic strength. This interesting observation could be attributed to the difference in ionic strength responsiveness for hydrophobic and electrostatic interactions. In this way, the well-tuned binding pattern could be achieved with optimized binding affinity by controlling the surface hydrophobicity of MNPs and ionic strength, thus endowing this system with great potential to fabricate separation and delivery system with high selectivity and efficiency.

Enhanced Luminescent Properties of Photo-Stable Copper Nanoclusters through Formation of "Protein-Corona"-Like Assemblies

In this study, interactions of synthesized copper nanoclusters (CuNCs) with a model transport protein, human serum albumin (HSA), have been systematically investigated by using various spectroscopic approaches. The interactions give rise to the formation of "protein-corona" like assemblies and the luminescence properties (both steady-state and time-resolved) are enhanced due to gradual adsorption of the protein on the surface of the NCs. The associated thermodynamics and binding parameters have been estimated resorting to luminescent experimental techniques as well as isothermal titration calorimetry (ITC) studies, indicating that every NC is surrounded by (4±1) protein molecules. The adsorption of HSA on the surface of the NCs has been characterized by dynamic light scattering (DLS) and time-resolved anisotropy measurements. Finally, fluorescence correlation spectroscopy (FCS) data substantiate the emergence of new "protein-corona" like assemblies resulting in slower translational diffusion motions and concomitant rise of the hydrodynamic diameters.

Specific Interaction Sites Determine Differential Adsorption of Protein Structural Isomers on Nanoparticle Surfaces

In biological systems, nanoparticles (NPs) elicit bioactivity upon interaction with proteins. As a result of post-translational modification, proteins occur in a variety of alternative covalent forms, including structural isomers, which present unique molecular surfaces. We aimed at a detailed description of the recognition of protein isomeric species by NP surfaces. The transient adsorption of isomeric ubiquitin (Ub) dimers by NPs was investigated by solution NMR spectroscopy. Lys63- and Lys48-linked Ub₂ were adsorbed by large anionic NPs with different affinities, whereas the binding strength was similar in the cases of smaller particles. After the incorporation of paramagnetic tags into NPs, the observed site-resolved paramagnetic footprints provided a high-resolution map of the different protein surfaces binding to NPs. The approach described could be extended to further protein isoforms and more specialized NP systems to allow better control of the interactions between NPs and protein targets.

Selective protein complexation and coacervation by polyelectrolytes

This review discusses the possible relationship between protein charge anisotropy, protein binding affinity, polymer structure, and selective phase separation. We hope that a fundamental understanding of primarily electrostatically driven protein-polyelectrolyte (PE) interactions can enable the prediction of selective protein binding, and hence selective coacervation through non-specific electrostatics. Such research will partially challenge the assumption that specific binding has to be realized through specific binding sites with a variety of short-range interactions and some geometric match. More specifically, the recent studies on selective binding of proteins by polyelectrolytes were examined from different assemblies in addition to the electrostatic features of proteins and PEs. At the end, the optimization of phase separation based on binding affinity for selective coacervation and some considerations relevant to using PEs for protein purification were also overviewed.

Interactions of PLGA nanoparticles with blood components: protein adsorption, coagulation, activation of the complement system and hemolysis studies

The intravenous administration of poly(lactic-co-glycolic) acid (PLGA) nanoparticles has been widely reported as a promising alternative for delivery of drugs to specific cells. However, studies on their interaction with diverse blood components using different techniques are still lacking. Therefore, in the present work, the interaction of PLGA nanoparticles with blood components was described using different complementary techniques. The influence of different encapsulated compounds/functionalizing agents on these interactions was also reported. It is worth noting that all these techniques can be simply performed, without the need for highly sophisticated apparatus or skills. Moreover, their transference to industries and application of quality control could be easily performed. Serum albumin was adsorbed onto all types of tested nanoparticles. The saturation concentration was dependent on the nanoparticle size. In contrast, fibrinogen aggregation was dependent on nanoparticle surface charge. The complement activation was also influenced by the nanoparticle functionalization; the presence of a functionalizing agent increased complement activation, while the addition of an encapsulated compound only caused a slight increase. None of the nanoparticles influenced the coagulation cascade at low concentrations. However, at high concentrations, cationized nanoparticles did activate the coagulation cascade. Interactions of nanoparticles with erythrocytes did not reveal any hemolysis. Interactions of PLGA nanoparticles with blood proteins depended both on the nanoparticle properties and the protein studied. Independent of their loading/surface functionalization, PLGA nanoparticles did not influence the coagulation cascade and did not induce hemolysis of erythrocytes; they could be defined as safe concerning induction of embolization and cell lysis.