A multiscale coarse-grained model to predict the molecular architecture and drug transport properties of modified chitosan hydrogels

Computer-aided nanodrug discovery: recent progress and future prospects

Nanodrugs, which utilise nanomaterials in disease prevention and therapy, have attracted considerable interest since their initial conceptualisation in the 1990s. Substantial efforts have been made to develop nanodrugs for overcoming the limitations of conventional drugs, such as low targeting efficacy, high dosage and toxicity, and potential drug resistance. Despite the significant progress that has been made in nanodrug discovery, the precise design or screening of nanomaterials with desired biomedical functions prior to experimentation remains a significant challenge. This is particularly the case with regard to personalised precision nanodrugs, which require the simultaneous optimisation of the structures, compositions, and surface functionalities of nanodrugs. The development of powerful computer clusters and algorithms has made it possible to overcome this challenge through in silico methods, which provide a comprehensive understanding of the medical functions of nanodrugs in relation to their physicochemical properties. In addition, machine learning techniques have been widely employed in nanodrug research, significantly accelerating the understanding of bio-nano interactions and the development of nanodrugs. This review will present a summary of the computational advances in nanodrug discovery, focusing on the understanding of how the key interfacial interactions, namely, surface adsorption, supramolecular recognition, surface catalysis, and chemical conversion, affect the therapeutic efficacy of nanodrugs. Furthermore, this review will discuss the challenges and opportunities in computer-aided nanodrug discovery, with particular emphasis on the integrated "computation + machine learning + experimentation" strategy that can potentially accelerate the discovery of precision nanodrugs.

Molecular modeling of the carbohydrate corona formation on a polyvinyl chloride nanoparticle and its impact on the adhesion to lipid bilayers

The pervasive presence of nanoplastics (NPs) in the environment has gained increasing attention due to their accumulation in living organisms. These emerging contaminants inevitably interact with extracellular polymeric substances along respiratory or gastrointestinal tracts, and diverse organic coating on the surface of NPs, known as bio- or eco-corona, is formed. Although its impact on altering the NP properties and potential cell internalization has been extensively examined, studies on its role in NP partitioning in the cell membrane are elusive yet. In this work, molecular dynamics is used to investigate the formation of chitosan (CT) corona centered on a polyvinyl chloride (PVC) nanoparticle and the uptake of the resulting complex onto lipid membranes. Coarse-grained models compatible with the newly developed Martini 3.0 force field are implemented for the two polymers employing the atomistic properties as targets in the parameterization. The reliability of the coarse-grained polymer models is demonstrated by reproducing the structural properties of the PVC melt and of solvated CT strands, as well as by determining the conformation adopted by the latter at the NP surface. Results show that the spontaneous binding of CT chains of high and intermediate protonation degrees led to the formation of soft and hard corona that modulates the interaction of PVC core with model membranes. The structural changes of the corona adsorbed at the lipid-water interface enable a subsequent transfer of the NP to the center of the saturated lipid membranes and a complete or partial transition to a snorkel conformation depending on the hydrophilic/hydrophobic balance in the CT-PVC complex. Overall, the computational investigation of the coarse-grained model system provides implications for understanding how the eco-corona development influences the uptake and implicit toxicology of NPs.

Peptide ligands targeting the vesicular stomatitis virus G (VSV-G) protein for the affinity purification of lentivirus particles

The recent uptick in the approval of ex vivo cell therapies highlights the relevance of lentivirus (LV) as an enabling viral vector of modern medicine. As labile biologics, however, LVs pose critical challenges to industrial biomanufacturing. In particular, LV purification-currently reliant on filtration and anion-exchange or size-exclusion chromatography-suffers from long process times and low yield of transducing particles, which translate into high waiting time and cost to patients. Seeking to improve LV downstream processing, this study introduces peptides targeting the enveloped protein Vesicular stomatitis virus G (VSV-G) to serve as affinity ligands for the chromatographic purification of LV particles. An ensemble of candidate ligands was initially discovered by implementing a dual-fluorescence screening technology and a targeted in silico approach designed to identify sequences with high selectivity and tunable affinity. The selected peptides were conjugated on Poros resin and their LV binding-and-release performance was optimized by adjusting the flow rate, composition, and pH of the chromatographic buffers. Ligands GKEAAFAA and SRAFVGDADRD were selected for their high product yield (50%-60% of viral genomes; 40%-50% of HT1080 cell-transducing particles) upon elution in PIPES buffer with 0.65 M NaCl at pH 7.4. The peptide-based adsorbents also presented remarkable values of binding capacity (up to 3·109 TU per mL of resin, or 5·1011 vp per mL of resin, at the residence time of 1 min) and clearance of host cell proteins (up to a 220-fold reduction of HEK293 HCPs). Additionally, GKEAAFAA demonstrated high resistance to caustic cleaning-in-place (0.5 M NaOH, 30 min) with no observable loss in product yield and quality.

Rational design and experimental evaluation of peptide ligands for the purification of adeno-associated viruses via affinity chromatography

Adeno-associated viruses (AAVs) have acquired a central role in modern medicine as delivery agents for gene therapies targeting rare diseases. While new AAVs with improved tissue targeting, potency, and safety are being introduced, their biomanufacturing technology is lagging. In particular, the AAV purification pipeline hinges on protein ligands for the affinity-based capture step. While featuring excellent AAV binding capacity and selectivity, these ligands require strong acid (pH <3) elution conditions, which can compromise the product's activity and stability. Additionally, their high cost and limited lifetime has a significant impact on the price tag of AAV-based therapies. Seeking to introduce a more robust and affordable affinity technology, this study introduces a cohort of peptide ligands that (i) mimic the biorecognition activity of the AAV receptor (AAVR) and anti-AAV antibody A20, (ii) enable product elution under near-physiological conditions (pH 6.0), and (iii) grant extended reusability by withstanding multiple regenerations. A20-mimetic CYIHFSGYTNYNPSLKSC and AAVR-mimetic CVIDGSQSTDDDKIC demonstrated excellent capture of serotypes belonging to distinct clones/clades - namely, AAV1, AAV2, AAV5, AAV6, AAV8, and AAV9. This corroborates the in silico models documenting their ability to target regions of the viral capsid that are conserved across all serotypes. CVIDGSQSTDDDKIC-Toyopearl resin features binding capacity (≈1014 vp mL-1 ) and product yields (≈60%-80%) on par with commercial adsorbents, and purifies AAV2 from HEK293 and Sf9 cell lysates with high recovery (up to 78%), reduction of host cell proteins (up to 700-fold), and high transduction activity (up to 65%).

Chitosan Polysaccharides from a Polarizable Multiscale Approach

We report simulations of chitosan polysaccharides in the aqueous phase, at infinite dilute conditions and zero ionic strength. Those simulations are performed by means of a polarizable multiscale modeling scheme that relies on a polarizable all atom force field to model solutes and on a polarizable solvent coarse grained approach. Force field parameters are assigned only from quantum chemistry ab initio data. We simulate chitosan monomer units, dimers and 50-long chains. Regarding the 50-long chains we simulate three sets of ten randomly built chain replica at three different pH conditions (corresponding to different chain protonation states, the chain degree of deacetylation is 85%). Our simulations show the persistence length of 50-long chitosan chains at strong acidic conditions (pH <5) to be 24 ± 2 nm (at weak/negligible ionic strength conditions), and to be 1 order of magnitude shorter at usual pH conditions. Our simulation data support the most recent simulation and experimental studies devoted to chitosan polysaccharides in the aqueous phase.

Analysis of diffusion of plant metabolites from polyethylene glycol hydrogels using free volume theory

The present work aims to comprehensively analyze the diffusion of plant metabolites from the polyethylene glycol (PEG) hydrogels for controlled release applications. For this study, a mathematical model based on free volume theory has been utilized to simulate the diffusion of low molecular weight plant metabolites. The results demonstrate that the mesh size of the crosslinked network, thereby the diffusion coefficient of the natural compound can be computed using the current framework. The proposed model has also been validated using the experimental data. The diffusion period has been observed to vary within a wide range of 3.42 h for Cinnamaldehyde to 49.25 h for Grandinin. An empirical parametric relationship between the diffusion time and molecular weight of both the hydrogels and natural compounds is established. It appears that the reported modeling approach will be clinically useful for improving the design of the sustained drug delivery systems.

Nucleoside-Based Supramolecular Hydrogels: From Synthesis and Structural Properties to Biomedical and Tissue Engineering Applications

Supramolecular hydrogels are of great interest in tissue scaffolding, diagnostics, and drug delivery due to their biocompatibility and stimuli-responsive properties. In particular, nucleosides are promising candidates as building blocks due to their manifold noncovalent interactions and ease of chemical modification. Significant progress in the field has been made over recent years to allow the use of nucleoside-based supramolecular hydrogels in the biomedical field, namely drug delivery and 3D bioprinting. For example, their long-term stability, printability, functionality, and bioactivity have been greatly improved by employing more than one gelator, incorporating different cations, including silver for antibacterial activity, or using additives such as boric acid or even biomolecules. This now permits their use as bioinks for 3D printing to produce cell-laden scaffolds with specified geometries and pore sizes as well as a homogeneous distribution of living cells and bioactive molecules. We have summarized the latest advances in nucleoside-based supramolecular hydrogels. Additionally, we discuss their synthesis, structural properties, and potential applications in tissue engineering and provide an outlook and future perspective on ongoing developments in the field.

A Core-Shell Approach for Systematically Coarsening Nanoparticle-Membrane Interactions: Application to Silver Nanoparticles

The continuous release of engineered nanomaterial (ENM) into the environment may bring about health concerns following human exposure. One important source of ENMs are silver nanoparticles (NPs) that are extensively used as anti-bacterial additives. The introduction of ENMs into the human body can occur via ingestion, skin uptake or the respiratory system. Therefore, evaluating how NPs translocate over bio-membranes is essential in assessing their primary toxicity. Unfortunately, data regarding membrane-NP interaction is still scarce, as is theoretical and in silico insight into what governs adhesion and translocation for the most relevant NPs and membranes. Coarse-grained (CG) molecular descriptions have the potential to alleviate this situation, but are hampered by the absence of a direct link to NP materials and membrane adhesion mechanisms. Here, we interrogate the relationship between the most common NP representation at the CG level and the adhesion characteristics of a model lung membrane. We find that this representation for silver NPs is non-transferable, meaning that a proper CG representation for one size is not suited for other sizes. We also identify two basic types of primary adhesion-(partial) NPs wrapping by the membrane and NP insertion into the membrane-that closely relate to the overall NP hydrophobicity and significantly differ in terms of lipid coatings. The proven non-transferability of the standard CG representation with size forms an inspiration for introducing a core-shell model even for bare NPs that are uniform in composition. Using existing all-atom molecular dynamics (MD) data as a reference, we show that this extension does allow us to reproduce size-dependent NP adhesion properties and lipid responses to NP binding at the CG level. The subsequent CGMD evaluation for 10 nm Ag NPs provides new insight into membrane binding for relevant NP sizes and into the role of water in trapping NPs into defected mixed monolayer-bilayer states. This development will be instrumental for simulating NP-membrane adhesion towards more experimentally relevant length and time scales for particular NP materials.

Chitosan characteristics in electrolyte solutions: Combined molecular dynamics modeling and slender body hydrodynamics

Molecular dynamics modeling was applied to predict chitosan molecule conformations, the contour length, the gyration radius, the effective cross-section and the density in electrolyte solutions. Using various experimental techniques the diffusion coefficient, the hydrodynamic diameter and the electrophoretic mobility of molecules were determined. This allowed to calculate the zeta potential, the electrokinetic charge and the effective ionization degree of the chitosan molecule as a function of pH and the temperature. The chitosan solution density and zero shear dynamic viscosity were also measured, which enabled to determine the intrinsic viscosity increment. The experimental results were quantitatively interpreted in terms of the slender body hydrodynamics exploiting molecule characteristics derived from the modeling. It is also confirmed that this approach can be successfully used for a proper interpretation of previous literature data obtained under various physicochemical conditions.

Chitosan: A versatile bio-platform for breast cancer theranostics

Breast cancer is considered one of the utmost neoplastic diseases globally, with a high death rate of patients. Over the last decades, many approaches have been studied to early diagnose and treat it, such as chemotherapy, hormone therapy, immunotherapy, and MRI and biomarker tests; do not show the optimal efficacy. These existing approaches are accompanied by severe side effects, thus recognizing these challenges, a great effort has been done to find out the new remedies for breast cancer. Main finding: Nanotechnology opened a new horizon to the treatment of breast cancer. Many nanoparticulate platforms for the diagnosis of involved biomarkers and delivering antineoplastic drugs are under either clinical trials or just approved by the Food and Drug Administration (FDA). It is well known that natural phytochemicals are successfully useful to treat breast cancer because these natural compounds are safer, available, cheaper, and have less toxic effects. Chitosan is a biocompatible and biodegradable polymer. Further, it has outstanding features, like chemical functional groups that can easily modify our interest with an exceptional choice of promising applications. Abundant studies were directed to assess the chitosan derivative-based nanoformulation's abilities in delivering varieties of drugs. However, the role of chitosan in diagnostics and theranostics not be obligated. The present servey will discuss the application of chitosan as an anticancer drug carrier such as tamoxifen, doxorubicin, paclitaxel, docetaxel, etc. and also, its role as a theranostics (i.e. photo-responsive and thermo-responsive) moieties. The therapeutic and theranostic potential of chitosan in cancer is promising and it seems that to have a good potential to get to the clinic.

Effect of water nanoconfinement on the dynamic properties of paramagnetic colloidal complexes

The anomalous behavior of confined water at the nanoscale has remarkable implications in a number of nanotechnological applications. In this work, we analyze the effect of water self-diffusion on the dynamic properties of a solvated gadolinium-based paramagnetic complex, typically used for contrast enhancement in magnetic resonance imaging. In particular, we examine the effect of silica-based nanostructures on water behavior in the proximity of the paramagnetic complex via atomistic simulations, and interpret the resulting tumbling dynamics in the light of the local solvent modification based on the Lipari-Szabo formalism and of the fractional Stokes-Einstein relation. It is found that the local water confinement induces an increased "stiffness" on the outer sphere of the paramagnetic complex, which eventually reduces its tumbling properties. These model predictions are found to explain well the relaxivity enhancement observed experimentally by confining paramagnetic complexes into porous nanoconstructs, and thus offer mechanistic guidelines to design improved contrast agents for imaging applications.