The effect of polymer coating on nanoparticles' interaction with lipid membranes studied by coarse-grained molecular dynamics simulations.

Nanoparticles' (NPs) permeation through cell membranes, whether it happens via passive or active transport, is an essential initial step for their cellular internalization. The NPs' surface coating impacts the way they translocate through the lipid bilayer and the spontaneity of the process. Understanding the molecular details of NPs' interaction with cell membranes allows the design of nanosystems with optimal characteristics for crossing the lipid bilayer: computer simulations are a powerful tool for this purpose. In this work, we have performed coarse-grained molecular dynamics simulations and free energy calculations on spherical titanium dioxide NPs conjugated with polymer chains of different chemical compositions. We have demonstrated that the hydrophobic/hydrophilic character of the chains, more than the nature of their terminal group, plays a crucial role in determining the NPs' interaction with the lipid bilayer and the thermodynamic spontaneity of NPs' translocation from water to the membrane. We envision that this computational work will be helpful to the experimental community in terms of the rational design of NPs for efficient cell membrane permeation.

Mechanism of RGD-conjugated nanodevice binding to its target protein integrin αVß3 by atomistic molecular dynamics and machine learning.

Active targeting strategies have been proposed to enhance the selective uptake of nanoparticles (NPs) by diseased cells, and recent experimental findings have proven the effectiveness of this approach. However, no mechanistic studies have yet revealed the atomistic details of the interactions between ligand-activated NPs and integrins. As a case study, here we investigate, by means of advanced molecular dynamics simulations (MD) and machine learning methods (namely equilibrium MD, binding free energy calculations and training of self-organized maps), the interaction of a cyclic-RGD-conjugated PEGylated TiO2 NP (the nanodevice) with the extracellular segment of integrin αVß3 (the target), the latter experimentally well-known to be over-expressed in several solid tumors. Firstly, we proved that the cyclic-RGD ligand binding to the integrin pocket is established and kept stable even in the presence of the cumbersome realistic model of the nanodevice. In this respect, the unsupervised machine learning analysis allowed a detailed comparison of the ligand/integrin binding in the presence and in the absence of the nanodevice, which unveiled differences in the chemical features. Then, we discovered that unbound cyclic RGDs conjugated to the NP largely contribute to the interactions between the nanodevice and the integrin. Finally, by increasing the density of cyclic RGDs on the PEGylated TiO2 NP, we observed a proportional enhancement of the nanodevice/target binding. All these findings can be exploited to achieve an improved targeting selectivity and cellular uptake, and thus a more successful clinical outcome.

Modeling Zeta Potential for Nanoparticles in Solution: Water Flexibility Matters.

Nonequilibrium molecular dynamics simulations were performed to study the electrokinetic properties of five mainstream TIPxP water models (namely, TIP3P-FB, TIP3Pm, TIP4P-FB, TIP4P-Ew, and TIP4P/2005) in NaCl aqueous solutions in the presence of a negatively charged TiO2 surface. The impact of solvent flexibility and system geometry on the electro-osmotic (EO) mobility and flow direction was systematically assessed and compared. We found that lack of water flexibility decelerates the forward EO flow of aqueous solutions at moderate (0.15 M) or high (0.30 M) NaCl concentrations, in some special cases to such an extent that EO flow reversal occurs. Zeta potential (ZP) values were then determined from the bulk EO mobilities using the Helmholtz-Smoluchowski formula. The straight comparison against available experimental data strongly suggests that water flexibility improves the ZP determination of NaCl solutions adjacent to a realistic TiO2 surface under neutral pH conditions.

Metadynamics simulations for the investigation of drug loading on functionalized inorganic nanoparticles.

Inorganic nanoparticles show promising properties that allow them to be efficiently used as drug carriers. The main limitation in this type of application is currently the drug loading capacity, which can be overcome with a proper functionalization of the nanoparticle surface. In this study, we present, for the first time, a computational approach based on metadynamics to estimate the binding free energy of the doxorubicin drug (DOX) to a functionalized TiO2 nanoparticle under different pH conditions. On a thermodynamic basis, we demonstrate the robustness of our approach to capture the overall mechanism behind the pH-triggered release of DOX due to environmental pH changes. Notably, binding free energy estimations align well with what is expected for a pH-sensitive drug delivery system. Based on our results, we envision the use of metadynamics as a promising computational tool for the rational design and in silico optimization of organic ligands with improved drug carrier properties.

Molecular Dynamics for the Optimal Design of Functionalized Nanodevices to Target Folate Receptors on Tumor Cells.

Atomistic details on the mechanism of targeting activity by biomedical nanodevices of specific receptors are still scarce in the literature, where mostly ligand/receptor pairs are modeled. Here, we use atomistic molecular dynamics (MD) simulations, free energy calculations, and machine learning approaches on the case study of spherical TiO2 nanoparticles (NPs) functionalized with folic acid (FA) as the targeting ligand of the folate receptor (FR). We consider different FA densities on the surface and different anchoring approaches, i.e., direct covalent bonding of FA γ-carboxylate or through polyethylene glycol spacers. By molecular docking, we first identify the lowest energy conformation of one FA inside the FR binding pocket from the X-ray crystal structure, which becomes the starting point of classical MD simulations in a realistic physiological environment. We estimate the binding free energy to be compared with the existing experimental data. Then, we increase complexity and go from the isolated FA to a nanosystem decorated with several FAs. Within the simulation time framework, we confirm the stability of the ligand-receptor interaction, even in the presence of the NP (with or without a spacer), and no significant modification of the protein secondary structure is observed. Our study highlights the crucial role played by the spacer, FA protonation state, and density, which are parameters that can be controlled during the nanodevice preparation step.

Molecular dynamics simulations of cRGD-conjugated PEGylated TiO2 nanoparticles for targeted photodynamic therapy.

The conjugation of high-affinity cRGD-containing peptides is a promising approach in nanomedicine to efficiently reduce off-targeting effects and enhance the cellular uptake by integrin-overexpressing tumor cells. Herein we utilize atomistic molecular dynamics simulations to evaluate key structural-functional parameters of these targeting ligands for an effective binding activity towards αVß3 integrins. An increasing number of cRGD ligands is conjugated to PEG chains grafted to highly curved TiO2 nanoparticles to unveil the impact of cRGD density on the ligand's presentation, stability, and conformation in an explicit aqueous environment. We find that a low density leads to an optimal spatial presentation of cRGD ligands out of the "stealth" PEGylated layer around the nanosystem, favoring a straight upward orientation and spaced distribution of the targeting ligands in the bulk-water phase. On the contrary, high densities favor over-clustering of cRGD ligands, driven by a concerted mechanism of enhanced ligand-ligand interactions and reduced water accessibility over the ligand's molecular surface. These findings strongly suggest that the ligand density modulation is a key factor in the design of cRGD-targeting nanodevices to maximize their binding efficiency into over-expressed αVß3 integrin receptors.

Multi-scale modeling of folic acid-functionalized TiO2 nanoparticles for active targeting of tumor cells.

Strategies based on the active targeting of tumor cells are emerging as smart and efficient nanomedical procedures. Folic acid (FA) is a vitamin and a well-established tumor targeting agent because of its strong affinity for the folate receptor (FR), which is an overexpressed protein on the cell membranes of the tumor cells. FA can be successfully anchored to several nanocarriers, including inorganic nanoparticles (NPs) based on transition metal oxides. Among them, TiO2 is extremely interesting because of its excellent photoabsorption and photocatalytic properties, which can be exploited in photodynamic therapy. However, it is not yet clear in which respects direct anchoring of FA to the NP or the use of spacers, based on polyethylene glycol (PEG) chains, are different and whether one approach is better than the other. In this work, we combine Quantum Mechanics (QM) and classical Molecular Dynamics (MD) to design and optimize the FA functionalization on bare and PEGylated TiO2 models and to study the dynamical behavior of the resulting nanoconjugates in a pure water environment and in physiological conditions. We observe that they are chemically stable, even under the effect of increasing temperature (up to 500 K). Using the results from long MD simulations (100 ns) and from free energy calculations, we determine how the density of FA molecules on the TiO2 NP and the presence of PEG spacers impact on the actual exposure of the ligands, especially by affecting the extent of FA-FA intermolecular interactions, which are detrimental for the targeting ability of FA towards the folate receptor. This analysis provides a solid and rational basis for experimentalists to define the optimal FA density and the more appropriate mode of anchoring to the carrier, according to the final purpose of the nanoconjugate.

Molecular dynamics simulations of doxorubicin in sphingomyelin-based lipid membranes.

Doxorubicin (DOX) is one of the most efficient antitumor drugs employed in numerous cancer therapies. Its incorporation into lipid-based nanocarriers, such as liposomes, improves the drug targeting into tumor cells and reduces drug side effects. The carriers' lipid composition is expected to affect the interactions of DOX and its partitioning into liposomal membranes. To get a rational insight into this aspect and determine promising lipid compositions, we use numerical simulations, which provide unique information on DOX-membrane interactions at the atomic level of resolution. In particular, we combine classical molecular dynamics simulations and free energy calculations to elucidate the mechanism of penetration of a protonated Doxorubicin molecule (DOX+) into potential liposome membranes, here modeled as lipid bilayers based on mixtures of phosphatidylcholine (PC), sphingomyelin (SM) and cholesterol lipid molecules, of different compositions and lipid phases. Moreover, we analyze DOX+ partitioning into relevant regions of SM-based lipid bilayer systems using a combination of free energy methods. Our results show that DOX+ penetration and partitioning are facilitated into less tightly packed SM-based membranes and are dependent on lipid composition. This work paves the way to further investigations of optimal formulations for lipid-based carriers, such as those associated with pH-responsive membranes.