Soysome: A Surfactant-Free, Fully Biobased, Self-Assembled Platform for Nanoscale Drug Delivery Applications

Metal-Organic Framework Induced Stabilization of Proteins in Polymeric Nanoparticles

Developing protein confinement platforms is an attractive research area that not only promotes protein delivery but also can result in artificial environment mimicking of the cellular one, impacting both the controlled release of proteins and the fundamental protein biophysics. Polymeric nanoparticles (PNPs) are attractive platforms to confine proteins due to their superior biocompatibility, low cytotoxicity, and controllable release under external stimuli. However, loading proteins into PNPs can be challenging due to the potential protein structural perturbation upon contacting the interior of PNPs. In this work, we developed a novel approach to encapsulate proteins in PNPs with the assistance of the zeolitic imidazolate framework (ZIF). Here, ZIF offers an additional protection layer to the target protein by forming the protein@ZIF composite via aqueous-phase cocrystallization. We demonstrated our platform using a model protein, lysozyme, and a widely studied PNP composed of poly(ethylene glycol)-poly(lactic-co-glycolic acid) (PEG-PLGA). A comprehensive study via standard loading and release tests as well as various spectroscopic techniques was carried out on lysozyme loaded onto PEG-PLGA with and without ZIF protection. As compared with the direct protein encapsulation, an additional layer with ZIF prior to loading offered enhanced loading capacity, reduced leaching, especially in the initial stage, led to slower release kinetics, and reduced secondary structural perturbation. Meanwhile, the function, cytotoxicity, and cellular uptake of proteins encapsulated within the ZIF-bound systems are decent. Our results demonstrated the use of ZIF in assisting in protein encapsulation in PNPs and established the basis for developing more sophisticated protein encapsulation platforms using a combination of materials of diverse molecular architectures and disciplines. As such, we anticipate that the protein-encapsulated ZIF systems will serve as future polymer protein confinement and delivery platforms for both fundamental biophysics and biochemistry research and biomedical applications where protein delivery is needed to support therapeutics and/or nutrients.

Organic and Biogenic Nanocarriers as Bio-Friendly Systems for Bioactive Compounds' Delivery: State-of-the Art and Challenges

"Green" strategies to build up novel organic nanocarriers with bioperformance are modern trends in nanotechnology. In this way, the valorization of bio-wastes and the use of living systems to develop multifunctional organic and biogenic nanocarriers (OBNs) have revolutionized the nanotechnological and biomedical fields. This paper is a comprehensive review related to OBNs for bioactives' delivery, providing an overview of the reports on the past two decades. In the first part, several classes of bioactive compounds and their therapeutic role are briefly presented. A broad section is dedicated to the main categories of organic and biogenic nanocarriers. The major challenges regarding the eco-design and the fate of OBNs are suggested to overcome some toxicity-related drawbacks. Future directions and opportunities, and finding "green" solutions for solving the problems related to nanocarriers, are outlined in the final of this paper. We believe that through this review, we will capture the attention of the readers and will open new perspectives for new solutions/ideas for the discovery of more efficient and "green" ways in developing novel bioperformant nanocarriers for transporting bioactive agents.

Biobased, Macro-, and Nanoscale Fungicide Delivery Approaches for Plant Fungi Control

In this report, two polymeric matrix systems at macro and nanoscales were prepared for efficacious fungicide delivery. The macroscale delivery systems used millimeter-scale, spherical beads composed of cellulose nanocrystals and poly(lactic acid). The nanoscale delivery system involved micelle-type nanoparticles, composed of methoxylated sucrose soyate polyols. Sclerotinia sclerotiorum (Lib.), a destructive fungus affecting high-value industrial crops, was used as a model pathogen against which the efficacy of these polymeric formulations was demonstrated. Commercial fungicides are applied on plants frequently to overcome the transmission of fungal infection. However, fungicides alone do not persist on the plants for a prolonged period due to environmental factors such as rain and airflow. There is a need to apply fungicides multiple times. As such, standard application practices generate a significant environmental footprint due to fungicide accumulation in soil and runoff in surface water. Thus, approaches are needed that can either increase the efficacy of commercially active fungicides or prolong their residence time on plants for sustained antifungal coverage. Using azoxystrobin (AZ) as a model fungicide and canola as a model crop host, we hypothesized that the AZ-loaded macroscale beads, when placed in contact with plants, will act as a depot to release the fungicide at a controlled rate to protect plants against fungal infection. The nanoparticle-based fungicide delivery approach, on the other hand, can be realized via spray or foliar applications. The release rate of AZ from macro- and nanoscale systems was evaluated and analyzed using different kinetic models to understand the mechanism of AZ delivery. We observed that, for macroscopic beads, porosity, tortuosity, and surface roughness governed the efficiency of AZ delivery, and for nanoparticles, contact angle and surface adhesion energy were directing the efficacy of the encapsulated fungicide. The technology reported here can also be translated to a wide variety of industrial crops for fungal protection. The strength of this study is the possibility of using completely plant-derived, biodegradable/compostable additive materials for controlled agrochemical delivery formulations, which will contribute to reducing the frequency of fungicide applications and the potential accumulation of formulation components in soil and water.

Self-Assembled Nanostructures from Amphiphilic Sucrose-Soyates for Solubilizing Hydrophobic Guest Molecules

We studied self-assembly and colloidal properties of poly(ethylene glycol) (pEG) conjugated sucrose soyate polyols (PSSP). These molecular platforms were synthesized by covalently connecting PEGs of different molecular weights (M_n) (12 and 16 ethylene oxide units) to epoxidized sucrose soyate (ESS). The synthesized PSSP products showed amphiphilicity, reduced water surface tension, and exhibited critical Aggregation Concentration (CAC) within the range of 0.3-0.4 mg/mL. We observed that PSSP self-assembles in water in the form of nanoparticles without the need of any cosolvents. These nanoparticles exhibited number-average hydrodynamic diameter of 120 ± 8 nm with a polydispersity index (PDI) of <0.3, and negatively charged surfaces. We also found out that PSSP nanoparticles can encapsulate and homogeneously distribute a hydrophobic model compound, such as a phthalocyanine dye, Solvent Blue-70 (BL-70), on a metal surface. Collectively, our studies explored and demonstrated the possibility of molecular diversification of biobased starting materials to form amphiphilic nanoparticles with industrially relevant colloidal and surface properties.

Eco-Friendly Production of AuNPs and Their Impact on the Oil Oxidative Stability

Vegetable oils have been used for different applications and, more recently, as an active host medium to obtain nanoparticles for employment in bionanotechnological applications. Nevertheless, oils are very susceptible to oxidation during production, storage, and transportation because of their chemical composition. Consequently, any modification in their production must be accompanied by an analysis of the oxidative stability. In this study, naked and biocompatible gold nanoparticles (AuNPs) were grown on sunflower oil during sputtering deposition using different deposition times. Size and morphology were determined by transmission electron microscopy (TEM) and their concentrations were found by inductively coupled plasma-optical emission spectroscopy (ICP-OES). Rancimat® method was employed to evaluate the AuNPs influence on the oxidative stability of the vegetable oil. Well-dispersed quasi-spherical NPs were produced with a mean diameter in the 2.9-3.7 nm range and they were concentration-dependent on the deposition time. A concentration of about 11 mg/L, 38 mg/L, and 225 mg/L of AuNPs was obtained for a deposition time of 5 min, 15 min, and 30 min, respectively. The results also revealed that AuNPs negatively affected the oxidative stability of the sunflower oil and exponentially reduced the induction period (IP) with the increase in AuNPs content. IP reductions of 63%, 77%, and 81% were determined for the AuNPs containing samples at 11 mg/L, 38 mg/L, and 225 mg/L. For the first time, it is reported that naked AuNPs promote the rapid degradation of vegetable oil and this points out the need for attention relative to the quality of vegetable oils used to host metal nanoparticles.

Optimizing ibuprofen concentration for rapid pharmacokinetics on biocompatible zinc-based MOF-74 and UTSA-74

Metal-organic frameworks (MOFs) have potential as drug carriers on the basis of their surface areas and pore volumes that allow for high loading and fast release. This study investigated two biocompatible MOFs - Zn MOF-74 and UTSA-74 - for ibuprofen delivery. The effect of drug loading was studied by impregnating the MOFs with 30, 50, and 80 wt% ibuprofen. The samples were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and N₂ physisorption. From SEM, the MOF structures were maintained at 30 wt% ibuprofen, however, became agglomerated at 50-80 wt% loading, as the drug deposited on the surface and adhered the particles to one another. In the physisorption measurements, the Zn MOF-74 samples decreased in surface area with ibuprofen loading, until they became zero at 80 wt%. In UTSA-74, the drug impregnation was less effective, as 35% of the original surface area was retained in the 80 wt% sample. On the basis of our drug release measurements, 50 wt% ibuprofen loading was found to be optimal on Zn MOF-74, as it gave rise to fast kinetics (k = 0.27 h^-1/2) and high drug concentrations within the first 10 h. In UTSA-74, the fastest release rate was observed at 30 wt% loading (k = 0.22 h^-1/2), as the poor impregnation efficiency blocked diffusion through the MOF pores at higher loading. Color changes of phosphate buffer saline (PBS) solutions at different time intervals also suggested that Zn MOF-74 decomposed during drug release, as it produced yellowing of the PBS solution. On the other hand, UTSA-74 did not discolor the PBS solution, and was concluded to not have dissolved during drug release. From these results, it was concluded that Zn MOF-74 was the superior drug carrier, as it could effectively deliver higher ibuprofen loadings and would dissolve in the process of drug release, thereby reducing its invasiveness in the human body.

Predicting coated-nanoparticle drug release systems with perturbation-theory machine learning (PTML) models

Nanoparticles (NPs) decorated with coating agents (polymers, gels, proteins, etc.) form Nanoparticle Drug Delivery Systems (DDNS), which are of high interest in nanotechnology and biomaterials science. There have been increasing reports of experimental data sets of biological activity, toxicity, and delivery properties of DDNS. However, these data sets are still dispersed and not as large as the datasets of DDNS components (NP and drugs). This has prompted researchers to train Machine Learning (ML) algorithms that are able to design new DDNS based on the properties of their components. However, most ML models reported up to date predictions of the specific activities of NP or drugs over a determined target or cell line. In this paper, we combine Perturbation Theory and Machine Learning (PTML algorithm) to train a model that is able to predict the best components (NP, coating agent, and drug) for DDNS design. In so doing, we downloaded a dataset of >30 000 preclinical assays of drugs from ChEMBL. We also downloaded an NP data set formed by preclinical assays of coated Metal Oxide Nanoparticles (MONPs) from public sources. Both the drugs and NP datasets of preclinical assays cover multiple conditions of assays that can be listed as two arrays, namely, cjdrug and cjNP. The cjdrug array includes >504 biological activity parameters (c0drug), >340 target proteins (c1drug), >650 types of cells (c2drug), >120 assay organisms (c3drug), and >60 assay strains (c4drug). On the other hand, the cjNP array includes 3 biological activity parameters (c0NP), 40 types of proteins (c1NP), 10 shapes of nanoparticles (c2NP), 6 assay media (c3NP), and 12 coating agents (c4NP). After downloading, we pre-processed both the data sets by separate calculation PT operators that are able to account for changes (perturbations) in the drug, coating agents, and NP chemical structure and/or physicochemical properties as well as for the assay conditions. Next, we carry out an information fusion process to form a final dataset of above 500 000 DDNS (drug + MONP pairs). We also trained other linear and non-linear PTML models using R studio scripts for comparative purposes. To the best of our knowledge, this is the first multi-label PTML model that is useful for the selection of drugs, coating agents, and metal or metal-oxide nanoparticles to be assembled in order to design new DDNS with optimal activity/toxicity profiles.