Probing the protein corona around charged macromolecules: interpretation of isothermal titration calorimetry by binding models and computer simulations

In situ characterization techniques of protein corona around nanomaterials

Nanoparticles (NPs) inevitably interact with proteins upon exposure to biological fluids, leading to the formation of an adsorption layer known as the "protein corona". This corona imparts NPs with a new biological identity, directly influencing their interactions with living systems and dictating their fates in vivo. Thus, gaining a comprehensive understanding of the dynamic interplay between NPs and proteins in biological fluids is crucial for predicting therapeutic effects and advancing the clinical translation of nanomedicines. Numerous methods have been established to decode the protein corona fingerprints. However, these methods primarily rely on prior isolation of NP-protein complex from the surrounding medium by centrifugation, resulting in the loss of outer-layer proteins that directly interact with the biological system and determine the in vivo fate of NPs. We discuss here separation techniques as well as in situ characterization methods tailored for comprehensively unraveling the inherent complexities of NP-protein interactions, highlighting the challenges of in situ protein corona characterization and its significance for nanomedicine development and clinical translation.

Binding of Proteins to Copolymers of Varying Charges and Hydrophobicity: A Molecular Mechanism and Computational Strategies

Because of their ability to selectively bind to a target protein, copolymer nanoparticles (NPs) containing a selected combination of hydrophobic and charged groups have been frequently reported as potent antibody-like analogues. However, due to the intrinsic disorder of the copolymer NP in terms of its random monomer sequence and the cross-linked copolymer matrix, the copolymer NP is indeed strikingly different from a well-folded protein antibody and the complexation between the copolymer NP and a target protein is likely not due to a lock-key type of interaction but possibly due to a novel and unexplored molecular mechanism. Here, we study a key biomarker protein, vimentin, interacting with a set of random copolymer chains using implicit-water explicit-ion coarse-grained (CG) molecular dynamics (MD) simulations along with biolayer interferometry (BLI) analysis. Due to the charge and hydrophobicity anisotropy on the vimentin dimer (VD) surface, a set of bound copolymers are found inhomogenously adsorbed on the VD, with energetic heterogeneity for different binding sites and cooperative effect in the adsorption. Increasing the charge or hydrophobicity of the copolymer may have different consequences on the adsorption. In this study, we found that with more copolymer charges, the protein coverage increases for copolymers of low hydrophobicity and decreases of high hydrophobicity, which is explained by the distribution and size of various functional patches on the VD in loading those copolymers. Employing a coverage-dependent Langmuir model, we propose a simulation protocol to address the full profile of the copolymer binding free energy through the fit to the simulated binding isotherm. The obtained results correlate well with those from the BLI experiment, indicating the significance of this method for the rational design of the copolymer NP with engineered protein binding affinity.

Interaction of Heparin with Proteins: Hydration Effects

We present a thermodynamic investigation of the interaction of heparin with lysozyme in the presence of potassium glutamate (KGlu). The binding constant K_b is measured by isothermal titration calorimetry (ITC) in a temperature range from 288 to 310 K for concentrations of KGlu between 25 and 175 mM. The free energy of binding ΔG_b derived from K_b is strongly decreasing with increasing concentration of KGlu, whereas the dependence of ΔG_b on temperature T is found to be small. The decrease of ΔG_b can be explained in terms of counterion release: Binding of lysozyme to the strong polyelectrolyte heparin liberates approximately three of the condensed counterions of heparin, thus increasing the entropy of the system. The dependence of ΔG_b on T, on the other hand, is traced back to a change of hydration of the protein and the polyelectrolyte upon complex formation. This dependence is quantitatively described by the parameter Δw that depends on T and vanishes at a characteristic temperature T₀. A comparison of the complex formation in the presence of KGlu with the one in the presence of NaCl demonstrates that the parameters related to hydration are changed considerably. The characteristic temperature T₀ in the presence of KGlu solutions is considerably smaller than that in the presence of NaCl solutions. The change of specific heat Δc_p is found to become more negative with increasing salt concentration: This finding agrees with the model-free analysis by the generalized van't Hoff equation. The entire analysis reveals a small but important change of the free energy of binding by hydration. It shows that these ion-specific Hofmeister effects can be modeled quantitatively in terms of a characteristic temperature T₀ and a parameter describing the dependence of Δc_p on salt concentration.

Development of the Sequential Binding Model and Application for Anticooperative Protein Adsorption onto Charged Dendrimers

The Langmuir binding model provides one of the simplest and elegant methods for characterizing an adsorption process. Despite its wide-ranging applications, enormous effort has been spent to further integrate complexity onto the standard Langmuir isotherm to incorporate a wide breadth of binding kinetics with the heterogeneity and cooperative effect among ligands and receptors. Here, we use statistical mechanics as a convenient theoretical framework to depict several adsorption processes on a Langmuir-like description. With regard to the system with a two-component mixture of macromolecular binders, we have derived the two-group sequential binding isotherm as an important extension of the original sequential model with more applications, including systems of non-identical binders. Via comparison of the Langmuir equilibrium with the Boltzmann equilibrium, for the first time the binding free energy defined in the Langmuir-like models can be meaningfully compared with simulations. In a practical example of the adsorption between the lysozyme protein and charged dendrimer, we have demonstrated how the calorimetry data of this system could be interpreted by the binding models described above, with an accurate description of the adsorption process, including the cooperative effect and dendrimer heterogeneity. Using the computer simulation as a benchmark, we also reveal and discuss the strengths and limitations of the proposed binding models. The entire analysis serves as a starting point for extending the standard Langmuir model to access more complicated binding processes.

Multiscale Modeling of Bio-Nano Interactions of Zero-Valent Silver Nanoparticles

Understanding the specifics of interaction between the protein and nanomaterial is crucial for designing efficient, safe, and selective nanoplatforms, such as biosensor or nanocarrier systems. Routing experimental screening for the most suitable complementary pair of biomolecule and nanomaterial used in such nanoplatforms might be a resource-intensive task. While a range of computational tools are available for prescreening libraries of proteins for their interactions with small molecular ligands, choices for high-throughput screening of protein libraries for binding affinities to new and existing nanomaterials are very limited. In the current work, we present the results of the systematic computational study of interaction of various biomolecules with pristine zero-valent noble metal nanoparticles, namely, AgNPs, by using the UnitedAtom multiscale approach. A set of blood plasma and dietary proteins for which the interaction with AgNPs was described experimentally were examined computationally to evaluate the performance of the UnitedAtom method. A set of interfacial descriptors (log P^NM, adsorption affinities, and adsorption affinity ranking), which can characterize the relative hydrophobicity/hydrophilicity/lipophilicity of the nanosized silver and its ability to form bio(eco)corona, was evaluated for future use in nano-QSAR/QSPR studies.

Combined first-principles statistical mechanics approach to sulfur structure in organic cathode hosts for polymer based lithium-sulfur (Li-S) batteries

Polymer-based batteries that utilize organic electrode materials are considered viable candidates to overcome the common drawbacks of lithium-sulfur (Li-S) batteries. A promising cathode can be developed using a conductive, flexible, and free-standing polymer, poly(4-thiophen-3-yl)benzenethiol) (PTBT), as the sulfur host material. By a vulcanization process, sulfur is embedded into this polymer. Here, we present a combination of electronic structure theory and statistical mechanics to characterize the structure of the initial state of the charged cathode on an atomic level. We perform a stability analysis of differently sulfurized TBT dimers as the basic polymer unit calculated within density-functional theory (DFT) and combine this with a statistical binding model for the binding probability distributions of the vulcanization process. From this, we deduce sulfur chain length ("rank") distributions and calculate the average sulfur rank depending on the sulfur concentration and temperature. This multi-scale approach allows us to bridge the gap between the local description of the covalent bonding process and the derivation of the macroscopic properties of the cathode. Our calculations show that the main reaction of the vulcanization process leads to high-probability states of sulfur chains cross-linking TBT units belonging to different polymer backbones, with a dominant rank around n = 5. In contrast, the connection of adjacent TBT units of the same polymer backbone by a sulfur chain is the side reaction. These results are experimentally supported by Raman spectroscopy.

Electrostatic Reaction Inhibition in Nanoparticle Catalysis

Electrostatic reaction inhibition in heterogeneous catalysis emerges if charged reactants and products with similar charges are adsorbed on the catalyst and thus repel the approaching reactants. In this work, we study the effects of electrostatic inhibition on the reaction rate of unimolecular reactions catalyzed on the surface of a spherical model nanoparticle using particle-based reaction-diffusion simulations. Moreover, we derive closed rate equations based on an approximate Debye-Smoluchowski rate theory, valid for diffusion-controlled reactions, and a modified Langmuir adsorption isotherm, relevant for reaction-controlled reactions, to account for electrostatic inhibition in the Debye-Hückel limit. We study the kinetics of reactions ranging from low to high adsorptions on the nanoparticle surface and from the surface- to diffusion-controlled limits for charge valencies 1 and 2. In the diffusion-controlled limit, electrostatic inhibition drastically slows down the reactions for strong adsorption and low ionic concentration, which is well described by our theory. In particular, the rate decreases with adsorption affinity because, in this case, the inhibiting products are generated at a high rate. In the (slow) reaction-controlled limit, the effect of electrostatic inhibition is much weaker, as semiquantitatively reproduced by our electrostatic-modified Langmuir theory. We finally propose and verify a simple interpolation formula that describes electrostatic inhibition for all reaction speeds ("diffusion-influenced" reactions) in general.

Molecular Modeling of Protein Corona Formation and Its Interactions with Nanoparticles and Cell Membranes for Nanomedicine Applications

The conformations and surface properties of nanoparticles have been modified to improve the efficiency of drug delivery. However, when nanoparticles flow through the bloodstream, they interact with various plasma proteins, leading to the formation of protein layers on the nanoparticle surface, called protein corona. Experiments have shown that protein corona modulates nanoparticle size, shape, and surface properties and, thus, influence the aggregation of nanoparticles and their interactions with cell membranes, which can increases or decreases the delivery efficiency. To complement these experimental findings and understand atomic-level phenomena that cannot be captured by experiments, molecular dynamics (MD) simulations have been performed for the past decade. Here, we aim to review the critical role of MD simulations to understand (1) the conformation, binding site, and strength of plasma proteins that are adsorbed onto nanoparticle surfaces, (2) the competitive adsorption and desorption of plasma proteins on nanoparticle surfaces, and (3) the interactions between protein-coated nanoparticles and cell membranes. MD simulations have successfully predicted the competitive binding and conformation of protein corona and its effect on the nanoparticle-nanoparticle and nanoparticle-membrane interactions. In particular, simulations have uncovered the mechanism regarding the competitive adsorption and desorption of plasma proteins, which helps to explain the Vroman effect. Overall, these findings indicate that simulations can now provide predications in excellent agreement with experimental observations as well as atomic-scale insights into protein corona formation and interactions.