Facilitating the Clinical Integration of Nanomedicines: The Roles of Theoretical and Computational Scientists

Diffusion of curcumin in PLGA-based carriers for drug delivery: a molecular dynamics study

CONTEXT

The rapid growth and diversification of drug delivery systems have been significantly supported by advancements in micro- and nano-technologies, alongside the adoption of biodegradable polymeric materials like poly(lactic-co-glycolic acid) (PLGA) as microcarriers. These developments aim to reduce toxicity and enhance target specificity in drug delivery. The use of in silico methods, particularly molecular dynamics (MD) simulations, has emerged as a pivotal tool for predicting the dynamics of species within these systems. This approach aids in investigating drug delivery mechanisms, thereby reducing the costs associated with design and prototyping. In this study, we focus on elucidating the diffusion mechanisms in curcumin-loaded PLGA particles, which are critical for optimizing drug release and efficacy in therapeutic applications.

METHODS

We utilized MD to explore the diffusion behavior of curcumin in PLGA drug delivery systems. The simulations, executed with GROMACS, modeled curcumin molecules in a representative volume element of PLGA chains and water, referencing molecular structures from the Protein Data Bank and employing the CHARMM force field. We generated PLGA chains of varying lengths using the Polymer Modeler tool and arranged them in a bulk-like environment with Packmol. The simulation protocol included steps for energy minimization, T and p equilibration, and calculation of the isotropic diffusion coefficient from the mean square displacement. The Taguchi method was applied to assess the effects of hydration level, PLGA chain length, and density on diffusion.

RESULTS

Our results provide insight into the influence of PLGA chain length, hydration level, and polymer density on the diffusion coefficient of curcumin, offering a mechanistic understanding for the design of efficient drug delivery systems. The sensitivity analysis obtained through the Taguchi method identified hydration level and PLGA density as the most significant input parameters affecting curcumin diffusion, while the effect of PLGA chain length was negligible within the simulated range. We provided a regression equation capable to accurately fit MD results. The regression equation suggests that increases in hydration level and PLGA density result in a decrease in the diffusion coefficient.

Computation-aided Design of Rod-Shaped Janus Base Nanopieces for Improved Tissue Penetration and Therapeutics Delivery

Despite the development of various drug delivery technologies, there remains a significant need for vehicles that can improve targeting and biodistribution in "hard-to-penetrate" tissues. Some solid tumors, for example, are particularly challenging to penetrate due to their dense extracellular matrix (ECM). In this study, we have formulated a new family of rod-shaped delivery vehicles named Janus base nanopieces (Rod JBNps), which are more slender than conventional spherical nanoparticles, such as lipid nanoparticles (LNPs). These JBNp nanorods are formed by bundles of DNA-inspired Janus base nanotubes (JBNts) with intercalated delivery cargoes. To develop this novel family of delivery vehicles, we employed a computation-aided design (CAD) methodology that includes molecular dynamics and response surface methodology. This approach precisely and efficiently guides experimental designs. Using an ovarian cancer model, we demonstrated that JBNps markedly improve penetration into the dense ECM of solid tumors, leading to better treatment outcomes compared to FDA-approved spherical LNP delivery. This study not only successfully developed a rod-shaped delivery vehicle for improved tissue penetration but also established a CAD methodology to effectively guide material design.

Ion-bridges and lipids drive aggregation of same-charge nanoparticles on lipid membranes

The control of the aggregation of biomedical nanoparticles (NP) in physiological conditions is crucial as clustering may change completely the way they interact with the biological environment. Here we show that Au nanoparticles, functionalized by an anionic, amphiphilic shell, spontaneously aggregate in fluid zwitterionic lipid bilayers. We use molecular dynamics and enhanced sampling techniques to disentangle the short-range and long-range driving forces of aggregation. At short inter-particle distances, ion-mediated, charge-charge interactions (ion bridging) stabilize the formation of large NP aggregates, as confirmed by cryo-electron microscopy. Lipid depletion and membrane curvature are the main membrane deformations driving long-range NP-NP attraction. Ion bridging, lipid depletion, and membrane curvature stem from the configurational flexibility of the nanoparticle shell. Our simulations show, more in general, that the aggregation of same-charge membrane inclusions can be expected as a result of intrinsically nanoscale effects taking place at the NP-NP and NP-bilayer soft interfaces.

Tuning cellular uptake of nanoparticles via ligand density: Contribution of configurational entropy

The bioactivity of nanoparticles (NPs) crucially depends on their ability to cross biological membranes. A fundamental understanding of cell-NP interaction is hence essential to improve the performance of the NP-based biomedical applications. Although extensive studies of cellular uptake have converged upon the idea that the uptake process is mainly regulated by the elastic deformation of the cell membrane or NP, recent experimental observations indicate the ligand density as another critical factor in modulating NP uptake into cells. In this study, we propose a theoretical model of the wrapping of an elastic vesicle NP by a finite lipid membrane to depict the relevant energetic and morphological evolutions during the wrapping process driven by forming receptor-ligand bonds. In this model, the deformations of the membrane and the vesicle NP are assumed to follow the continuum Canham-Helfrich framework, whereas the change of configurational entropy of receptors is described from statistical thermodynamics. Results show that the ligand density strongly affects the binding energy and configurational entropy of free receptors, thereby altering the morphology of the vesicle-membrane system in the steady wrapping state. For the wrapping process by the finite lipid membrane, we also find that there exists optimal ligand density for the maximum wrapping degree. These predictions are consistent with relevant experimental observations reported in the literature. We have further observed that there are transitions of various wrapping phases (no wrapping, partial wrapping, and full wrapping) in terms of ligand density, membrane tension, and molecular binding energy. In particular, the ligand and receptor shortage regimes for the small and high ligand density are, respectively, identified. These results may provide guidelines for the rational design of nanocarriers for drug delivery.

Role of Ligand Distribution in the Cytoskeleton-Associated Endocytosis of Ellipsoidal Nanoparticles

Nanoparticle (NP)–cell interaction mediated by receptor–ligand bonds is a crucial phenomenon in pathology, cellular immunity, and drug delivery systems, and relies strongly on the shape of NPs and the stiffness of the cell. Given this significance, a fundamental question is raised on how the ligand distribution may affect the membrane wrapping of non-spherical NPs under the influence of cytoskeleton deformation. To address this issue, in this work we use a coupled elasticity–diffusion model to systematically investigate the role of ligand distribution in the cytoskeleton-associated endocytosis of ellipsoidal NPs for different NP shapes, sizes, cytoskeleton stiffness, and the initial receptor densities. In this model, we have taken into account the effects of receptor diffusion, receptor–ligand binding, cytoskeleton and membrane deformations, and changes in the configuration entropy of receptors. By solving this model, we find that the uptake process can be significantly influenced by the ligand distribution. Additionally, there exists an optimal state of such a distribution, which corresponds to the fastest uptake efficiency and depends on the NP aspect ratio and cytoskeleton stiffness. We also find that the optimal distribution usually needs local ligand density to be sufficiently high at the large curvature region. Furthermore, the optimal state of NP entry into cells can tolerate slight changes to the corresponding optimal distribution of the ligands. The tolerance to such a change is enhanced as the average receptor density and NP size increase. These results may provide guidelines to control NP–cell interactions and improve the efficiency of target drug delivery systems.

Enhanced Drug Delivery to Solid Tumors via Drug-Loaded Nanocarriers: An Image-Based Computational Framework

Objective

Nano-sized drug delivery systems (NSDDSs) offer a promising therapeutic technology with sufficient biocompatibility, stability, and drug-loading rates towards efficient drug delivery to solid tumors. We aim to apply a multi-scale computational model for evaluating drug delivery to predict treatment efficacy.

Methodology

Three strategies for drug delivery, namely conventional chemotherapy (one-stage), as well as chemotherapy through two- and three-stage NSDDSs, were simulated and compared. A geometric model of the tumor and the capillary network was obtained by processing a real image. Subsequently, equations related to intravascular and interstitial flows as well as drug transport in tissue were solved by considering real conditions as well as details such as drug binding to cells and cellular uptake. Finally, the role of periodic treatments was investigated considering tumor recurrence between treatments. The impact of different parameters, nanoparticle (NP) size, binding affinity of drug, and the kinetics of release rate, were additionally investigated to determine their therapeutic efficacy.

Results

Using NPs considerably increases the fraction of killed cells (FKCs) inside the tumor compared to conventional chemotherapy. Tumoral FKCs for two-stage DDS with smaller NP size (20nm) is higher than that of larger NPs (100nm), in all investigate release rates. Slower and continuous release of the chemotherapeutic agents from NPs have better treatment outcomes in comparison with faster release rate. In three-stage DDS, for intermediate and higher binding affinities, it is desirable for the secondary particle to be released at a faster rate, and the drug with slower rate. In lower binding affinities, high release rates have better performance. Results also demonstrate that after 5 treatments with three-stage DDS, 99.6% of tumor cells (TCs) are killed, while two-stage DDS and conventional chemotherapy kill 95.6% and 88.5% of tumor cells in the same period, respectively.

Conclusion

The presented framework has the potential to enable decision making for new drugs via computational modeling of treatment responses and has the potential to aid oncologists with personalized treatment plans towards more optimal treatment outcomes.

Capsules Rheology in Carreau-Yasuda Fluids

In this paper, a Multi Relaxation Time Lattice Boltzmann scheme is used to describe the evolution of a non-Newtonian fluid. Such method is coupled with an Immersed-Boundary technique for the transport of arbitrarily shaped objects navigating the flow. The no-slip boundary conditions on immersed bodies are imposed through a convenient forcing term accounting for the hydrodynamic force generated by the presence of immersed geometries added to momentum equation. Moreover, such forcing term accounts also for the force induced by the shear-dependent viscosity model characterizing the non-Newtonian behavior of the considered fluid. Firstly, the present model is validated against well-known benchmarks, namely the parabolic velocity profile obtained for the flow within two infinite laminae for five values of the viscosity model exponent, n = 0.25, 0.50, 0.75, 1.0, and 1.5. Then, the flow within a squared lid-driven cavity for Re = 1000 and 5000 (being Re the Reynolds number) is computed as a function of n for a shear-thinning (n < 1) fluid. Indeed, the local decrements in the viscosity field achieved in high-shear zones implies the increment in the local Reynolds number, thus moving the position of near-walls minima towards lateral walls. Moreover, the revolution under shear of neutrally buoyant plain elliptical capsules with different Aspect Ratio (AR = 2 and 3) is analyzed for shear-thinning (n < 1), Newtonian (n = 1), and shear-thickening (n > 1) surrounding fluids. Interestingly, the power law by Huang et al. describing the revolution period of such capsules as a function of the Reynolds number and the existence of a critical value, Rec, after which the tumbling is inhibited in confirmed also for non-Newtonian fluids. Analogously, the equilibrium lateral position yeq of such neutrally buoyant capsules when transported in a plane-Couette flow is studied detailing the variation of yeq as a function of the Reynolds number as well as of the exponent n.

Multifunctional peptides for tumor therapy

Controlled nano-systems for drug delivery are designed to deliver therapeutical drugs to desirable sites on demand. Due to the diverse physiological functions of peptides, it is reasonable to introduce peptides into anti-tumor nano-system. The integration of peptides into nanomaterials has complementary advantages, which not only avoids the rapid degradation of peptides in vivo, but also improves the intelligence and functionality of the nano-system. We summarized the functional peptides with targeting and stimulus-responsive properties, and the present review outlined the most relevant and recent developed peptide-based multifunctional nanomaterials for tumor therapy.

Vascular journey and adhesion mechanics of micro-sized carriers in narrow capillaries

In this work a Lattice Boltzmann-Immersed Boundary method is used for predicting the dynamics of rigid and deformable adhesive micro-carriers (1 μm) navigating a capillary by the size of 10 μm with 20% hematocrit. Red cells and particles are modeled as a collection of mass-spring elements responding to a bending potential, an elastic potential and total enclosed area conservation constraint. Furthermore, particle surfaces are uniformly decorated with adhesive molecules (ligands) interacting with receptors disposed on the walls. Particle adhesion is modeled as a short-range ligad-receptor interaction and in term of formation and destruction probability functions that discriminate whether a chemical bond can be formed or destroyed. If a bond is established an attractive elastic force is activated. Particle transport and adhesion are characterized in terms of their ability to reach the capillary peripheries (margination rate) and firmly adhere the vasculature. This analysis is carried out systematically by varying particles' and cells' releasing positions and stiffness (Ca = 0 and 10^-2). Moreover, three rigid and soft representative particles are transported on a finer mesh (Δx = 15 nm) and the chemical strength of their adhesive coating is varied (σ = 0.5, 1.0, and 2.0) to precisely analyze the resulting adhesion mechanics. Stiffness is found to weakly influence the margination rate while significantly affect the ability of such constructs to efficiently interact with the endothelium by forming stable chemical bonds.

Improving nanotherapy delivery and action through image-guided systems pharmacology

Despite recent advances in the translation of therapeutic nanoparticles (TNPs) into the clinic, the field continues to face challenges in predictably and selectively delivering nanomaterials for the treatment of solid cancers. The concept of enhanced permeability and retention (EPR) has been coined as a convenient but simplistic descriptor of high TNP accumulation in some tumors. However, in practice EPR represents a number of physiological variables rather than a single one (including dysfunctional vasculature, compromised lymphatics and recruited host cells, among other aspects of the tumor microenvironment) — each of which can be highly heterogenous within a given tumor, patient and across patients. Therefore, a clear need exists to dissect the specific biophysical factors underlying the EPR effect, to formulate better TNP designs, and to identify patients with high-EPR tumors who are likely to respond to TNP. The overall pharmacology of TNP is governed by an interconnected set of spatially defined and dynamic processes that benefit from a systems-level quantitative approach, and insights into the physiology have profited from the marriage between in vivo imaging and quantitative systems pharmacology (QSP) methodologies. In this article, we review recent developments pertinent to image-guided systems pharmacology of nanomedicines in oncology. We first discuss recent developments of quantitative imaging technologies that enable analysis of nanomaterial pharmacology at multiple spatiotemporal scales, and then examine reports that have adopted these imaging technologies to guide QSP approaches. In particular, we focus on studies that have integrated multi-scale imaging with computational modeling to derive insights about the EPR effect, as well as studies that have used modeling to guide the manipulation of the EPR effect and other aspects of the tumor microenvironment for improving TNP action. We anticipate that the synergistic combination of imaging with systems-level computational methods for effective clinical translation of TNPs will only grow in relevance as technologies increase in resolution, multiplexing capability, and in the ability to examine heterogeneous behaviors at the single-cell level.

Leaf-Inspired Authentically Complex Microvascular Networks for Deciphering Biological Transport Process

The vascular transport of molecules, cells, and nanoconstructs is a fundamental biophysical process impacting tissue regeneration, delivery of nutrients and therapeutic agents, and the response of the immune system to external pathogens. This process is often studied in single-channel microfluidic devices lacking the complex tridimensional organization of vascular networks. Here, soft lithography is employed to replicate the vein system of a Hedera elix leaf on a polydimethilsiloxane (PDMS) template. The replica is then sealed and connected to an external pumping system to realize an authentically complex microvascular network. This satisfies energy minimization criteria by Murray's law and comprises a network of channels ranging in size from capillaries (∼50 μm) to large arterioles and venules (∼400 μm). Micro-PIV (micro-particle image velocimetry) analysis is employed to characterize flow conditions in terms of streamlines, fluid velocity, and flow rates. To demonstrate the ability to reproduce physiologically relevant transport processes, two different applications are demonstrated: vascular deposition of tumor cells and lysis of blood clots. To this end, conditions are identified to culture cells within the microvasculature and realize a confluent endothelial monolayer. Then, the vascular deposition of circulating breast (MDA-MB 231) cancer cells is documented throughout the network under physiologically relevant flow conditions. Firm cell adhesion mostly occurs in channels with low mean blood velocity. As a second application, blood clots are formed within the chip by mixing whole blood with a thrombin solution. After demonstrating the blood clot stability, tissue plasminogen activator (tPA) and tPA-carrying nanoconstructs (tPA-DPNs) are employed as thrombolytics. In agreement with previous data, clot dissolution is equally induced by tPA and tPA-DPNs. The proposed leaf-inspired chip can be efficiently used to study a variety of vascular transport processes in complex microvascular networks, where geometry and flow conditions can be modulated and monitored throughout the experimental campaign.

Tailoring the Chemical Modification of Chitosan Hydrogels to Fine-Tune the Release of a Synergistic Combination of Chemotherapeutics

Combination chemotherapy with a defined ratio and sequence of drug release is a clinically established and effective route to treat advanced solid tumors. In this context, a growing body of literature demonstrates the potential of hydrogels constructed with chemically modified polysaccharides as depots for controlled release of chemotherapeutics. Identifying the appropriate modification in terms of physicochemical properties of the functional group and its degree of substitution (χ) to achieve the desired release profile for multiple drugs is, however, a complex multivariate problem. To address this issue, we have developed a computational toolbox that models the migration of a drug pair through a hydrated network of polysaccharide chains modified with hydrophobic moieties. In this study, we chose doxorubicin (DOX) and Gemcitabine (GEM) as model drugs, as their synergistic effect against breast cancer has been thoroughly investigated, and chitosan as the model polymer. Our model describes how the modification of chitosan chains with acetyl, butanoyl, and heptanoyl moieties at different values χ governs both the structure of the hydrogel network and drug migration through it. Our experimental data confirm the in silico predictions for both single- and dual-drug release and, most notably, the counterintuitive inversion of release vs χ that occurs when switching from a single- to a dual-drug system. Consensus between predicted and experimental data indicates that acetyl modifications (χ = 32-42%) and butanoyl modifications (χ = 19-24%) provide synergistic GEM/DOX release molar ratios (i.e., 5-10). Collectively, these results demonstrate the potential of this model in guiding the design of chemotherapeutic hydrogels to combat cancer.

Multiscale Molecular Dynamics Simulation of Multiple Protein Adsorption on Gold Nanoparticles

A multiscale molecular dynamics simulation study has been carried out in order to provide in-depth information on the adsorption of hemoglobin, myoglobin, and trypsin over citrate-capped AuNPs of 15 nm diameter. In particular, determinants for single proteins adsorption and simultaneous adsorption of the three types of proteins considered have been studied by Coarse-Grained and Meso-Scale molecular simulations, respectively. The results, discussed in the light of the controversial experimental data reported in the current experimental literature, have provided a detailed description of the (i) recognition process, (ii) number of proteins involved in the early stages of corona formation, (iii) protein competition for AuNP adsorption, (iv) interaction modalities between AuNP and protein binding sites, and (v) protein structural preservation and alteration.

Exploring the Heterogeneity of Nanoparticles in Their Interactions with Plasma Coagulation Factor XII

Tuning the characteristics of nanoparticles (NPs) would be promising in improving their biocompatibilities, regarding biosafety and nanodrug considerations. Due to the high priority of the artificial NPs in contacting the circulatory system, understanding their interactions with plasma zymogens is of great importance. Four kinds of NPs, including 5 nm gold NPs (GNP-5), 5 and 20 nm silver NPs (SNP-5, SNP-20), and 20 nm silica NPs (SiNP-20), were investigated for their interactions with the coagulation factor XII (FXII). GNP-5 adsorbed FXII in a standing-up mode, and exhibited high binding affinity for the heavy chain of the protein without altering its secondary structure or inducing its activation. In contrast to GNP-5, FXII adsorption on the other tested NPs was in a lying-down mode, and their interactions with FXII induced its conformational changes, thus causing the evident zymogen cleavage. The structural alterations and activation of FXII induced by the NPs exhibited in specific surface area dependent manners, which were related with different NP cores and sizes. Additionally, the enzymatic activity of α-FXIIa was also influenced by NP incubation, and the alterations were dependent on the specific characters of the NPs as evidenced by the enzymatic inhibition effect of GNP-5 (noncompetitive) and SNP-5 (competitive), and enhanced enzymatic catalysis abilities of SNP-20 and SiNP-20. The interesting findings on the heterogeneity of NPs in their interactions with plasma FXII not only revealed the underlying mechanism for NP-triggered hematological responses, but also suggested the crucial role of tuning NP parameters in their potential bioapplication, like nanodrug design.

Role of Ligand Conformation on Nanoparticle-Protein Interactions

Engineered biomedical nanoparticles (NPs) administered via intravenous routes are prone to associate to serum proteins. The protein corona can mask the NP surface functionalization and hamper the delivery of the NP to its biological target. The design of corona-free NPs relies on our understanding of the chemical-physical features of the NP surface driving the interaction with serum proteins. Here, we address, by computational means, the interaction between human serum albumin (HSA) and a prototypical monolayer-protected Au nanoparticle. We show that both the chemical composition (charge, hydrophobicity) and the conformational preferences of the ligands decorating the NP surface affect the NP propensity to bind HSA.

Progress in ligand design for monolayer-protected nanoparticles for nanobio interfaces

Ligand-functionalized inorganic nanoparticles, also known as monolayer-protected nanoparticles, offer great potential as vehicles for in vivo delivery of drugs, genes, and other therapeutics. These nanoparticles offer highly customizable chemistries independent of the size, shape, and functionality imparted by the inorganic core. Their success as drug delivery agents depends on their interaction with three major classes of biomolecules: nucleic acids, proteins, and membranes. Here, the authors discuss recent advances and open questions in the field of nanoparticle ligand design for nanomedicine, with a focus on atomic-scale interactions with biomolecules. While the importance of charge and hydrophobicity of ligands for biocompatibility and cell internalization has been demonstrated, ligand length, flexibility, branchedness, and other properties also influence the properties of nanoparticles. However, a comprehensive understanding of ligand design principles lies in the cost associated with synthesizing and characterizing diverse ligand chemistries and the ability to carefully assess the structural integrity of biomolecules upon interactions with nanoparticles.

Computational approaches to cell-nanomaterial interactions: keeping balance between therapeutic efficiency and cytotoxicity

Owing to their unique properties, nanomaterials have been widely used in biomedicine since they have obvious inherent advantages over traditional ones. However, nanomaterials may also cause dysfunction in proteins, genes and cells, resulting in cytotoxic and genotoxic responses. Recently, more and more attention has been paid to these potential toxicities of nanomaterials, especially to the risks of nanomaterials to human health and safety. Therefore, when using nanomaterials for biomedical applications, it is of great importance to keep the balance between therapeutic efficiency and cytotoxicity (i.e., increase the therapeutic efficiency as well as decrease the potential toxicity). This requires a deeper understanding of the interactions between various types of nanomaterials and biological systems at the nano/bio interface. In this review, from the point of view of theoretical researchers, we will present the current status regarding the physical mechanism of cytotoxicity caused by nanomaterials, mainly based on recent simulation results. In addition, the strategies for minimizing the nanotoxicity naturally and artificially will also be discussed in detail. Furthermore, we should notice that toxicity is not always bad for clinical use since causing the death of specific cells is the main way of treating disease. Enhancing the targeting ability of nanomaterials to diseased cells and minimizing their side effects on normal cells will always be hugely challenging issues in nanomedicine. By combining the latest computational studies with some experimental verifications, we will provide special insights into recent advances regarding these problems, especially for the design of novel environment-responsive nanomaterials.

pH-Sensitive Reversible Programmed Targeting Strategy by the Self-Assembly/Disassembly of Gold Nanoparticles

A reversible programmed targeting strategy could achieve high tumor accumulation due to its long blood circulation time and high cellular internalization. Here, targeting ligand-modified poly(ethylene glycol) (PEG-ligand), dibutylamines (Bu), and pyrrolidinamines (Py) were introduced on the surface of gold nanoparticles (Au NPs) for reversible shielding/deshielding of the targeting ligands by pH-responsive self-assembly. Hydrophobic interaction and steric repulsion are the main driving forces for the self-assembly/disassembly of Au NPs. The precise self-assembly (pH ≥ 7.2) and disassembly (pH ≤ 6.8) of Au NPs with different ligands could be achieved by fine-tuning the modifying molar ratio of Bu and Py (R_m), which followed the formula R_m = 1/(-0.0013X² + 0.0323X + 1), in which X is the logarithm of the partition coefficient of the targeting ligand. The assembled/disassembled behavior of Au NPs at pH 7.2 and 6.8 was confirmed by transmission electron microscopy and dynamic light scattering. Enzyme-linked immunosorbent assays and cellular uptake studies showed that the ligands could be buried inside the assembly and exposed when disassembled. More importantly, this process was reversible, which provides the possibility of prolonging blood circulation by shielding ligands associated with the NPs that were effused from tumor tissue.

Effects of ligand distribution on receptor-diffusion-mediated cellular uptake of nanoparticles

Biophysical-factor-dependent cellular uptake of nanoparticles (NPs) through receptor-diffusion-mediated endocytosis bears significance in pathology, cellular immunity and drug-delivery systems. Advanced nanotechnology of NP synthesis provides methods for modifying NP surface with different ligand distributions. However, no report discusses effects of ligand distribution on NP surface on receptor-diffusion-mediated cellular uptake. In this article, we used a statistical dynamics model of receptor-diffusion-mediated endocytosis to examine ligand-distribution-dependent cellular uptake dynamics by considering that ligand-receptor complexes drive engulfing to overcome resistance to membrane deformation and changes in configuration entropy of receptors. Results showed that cellular internalization of NPs strongly depended on ligand distribution and that cellular-uptake efficiency of NPs was high when ligand distribution was within a range around uniform distribution. This feature of endocytosis ensures robust infection ability of viruses to enter host cells. Interestingly, results also indicated that optimal ligand distribution associated with highest cellular-uptake efficiency slightly depends on distribution pattern of ligands and density of receptors, and the optimal distribution becomes uniform when receptor density is sufficiently large. Position of initial contact point is also a factor affecting dynamic wrapping. This study explains why most enveloped viruses present almost homogeneous ligand distribution and is useful in designing controlled-release drug-delivery systems.

Nanomedicine 2.0

Nanotechnology can profoundly change the way we diagnose and treat diseases, but the ability to control how engineered nanoparticles behave within the body remains largely elusive. This Commentary describes the progress and limitations of nanomedicine and the research and experimental philosophies that should be considered in our quest to advance nanotechnology to the clinic.

Predicting different adhesive regimens of circulating particles at blood capillary walls

A fundamental step in the rational design of vascular targeted particles is the firm adhesion at the blood vessel walls. Here, a combined lattice Boltzmann-immersed boundary model is presented for predicting the near-wall dynamics of circulating particles. A moving least squares algorithm is used to reconstruct the forcing term accounting for the immersed particle, whereas ligand-receptor binding at the particle-wall interface is described via forward and reverse probability distributions. First, it is demonstrated that the model predicts with good accuracy the rolling velocity of tumor cells over an endothelial layer in a microfluidic channel. Then, particle-wall interactions are systematically analyzed in terms of particle geometries (circular, elliptical with aspect ratios 2 and 3), surface ligand densities (0.3, 0.5, 0.7 and 0.9), ligand-receptor bond strengths (1 and 2) and Reynolds numbers (Re = 0.01, 0.1 and 1.0). Depending on these conditions, four different particle-wall interaction regimens are identified, namely not adhering, rolling, sliding and firmly adhering particles. The proposed computational strategy can be efficiently used for predicting the near-wall dynamics of particles with arbitrary geometries and surface properties and represents a fundamental tool in the rational design of particles for the specific delivery of therapeutic and imaging agents.