Hierarchical design of hyaluronic acid-peptide constructs for glioblastoma targeting: Combining insights from NMR and molecular dynamics simulations

Structural Analysis and Classification of Low-Molecular-Weight Hyaluronic Acid by Near-Infrared Spectroscopy: A Comparison between Traditional Machine Learning and Deep Learning

Confusing low-molecular-weight hyaluronic acid (LMWHA) from acid degradation and enzymatic hydrolysis (named LMWHA-A and LMWHA-E, respectively) will lead to health hazards and commercial risks. The purpose of this work is to analyze the structural differences between LMWHA-A and LMWHA-E, and then achieve a fast and accurate classification based on near-infrared (NIR) spectroscopy and machine learning. First, we combined nuclear magnetic resonance (NMR), Fourier transform infrared (FTIR) spectroscopy, two-dimensional correlated NIR spectroscopy (2DCOS), and aquaphotomics to analyze the structural differences between LMWHA-A and LMWHA-E. Second, we compared the dimensionality reduction methods including principal component analysis (PCA), kernel PCA (KPCA), and t-distributed stochastic neighbor embedding (t-SNE). Finally, the differences in classification effect of traditional machine learning methods including partial least squares-discriminant analysis (PLS-DA), support vector classification (SVC), and random forest (RF) as well as deep learning methods including one-dimensional convolutional neural network (1D-CNN) and long short-term memory (LSTM) were compared. The results showed that genetic algorithm (GA)-SVC and RF were the best performers in traditional machine learning, but their highest accuracy in the test dataset was 90%, while the accuracy of 1D-CNN and LSTM models in the training dataset and test dataset classification was 100%. The results of this study show that compared with traditional machine learning, the deep learning models were better for the classification of LMWHA-A and LMWHA-E. Our research provides a new methodological reference for the rapid and accurate classification of biological macromolecules.

Extracellular matrix degrading enzyme with stroma-targeting peptides enhance the penetration of liposomes into tumors

Various anti-tumor nanomedicines have been developed based on the enhanced permeability and retention effect. However, the dense extracellular matrix (ECM) in tumors remains a major barrier for the delivery and accumulation of nanoparticles into tumors. While ECM-degrading enzymes, such as collagenase, hyaluronidase, and bromelain, have been used to facilitate the accumulation of nanoparticles, serious side effects arising from the current non-tumor-specific delivery methods limit their clinical applications. Here, we report targeted delivery of bromelain into tumor tissues through its covalent attachment to a hyaluronic acid (HA)-peptide conjugate with tumor ECM targeting ability. The ECM targeting peptide, collagen type IV-binding peptide (C4BP), was chosen from six candidate-peptides based on their ability to bind to frozen sections of triple-negative breast cancer, 4T1 tumor ex vivo. The HA- C4BP conjugate showed a significant increase in tumor accumulation in 4T1-bearing mice after intravenous administration compared to unmodified HA. We further demonstrated that the systemic administration of bromelain conjugated C4BP-HA (C4BP-HA-Bro) potentiates the anti-tumor efficacy of liposomal doxorubicin. C4BP-HA-Bro decreased the number and length of collagen fibers and improved the distribution of doxorubicin within the tumor. No infusion reaction was noted after delivery of C4BP-HA-Bro. C4BP-HA thus offers a potential for effective and safe delivery of bromelain for improved intratumoral delivery of therapeutics.

Peptides as Pharmacological Carriers to the Brain: Promises, Shortcomings and Challenges

Central nervous system (CNS) diseases are among the most difficult to treat, mainly because the vast majority of the drugs fail to cross the blood-brain barrier (BBB) or to reach the brain at concentrations adequate to exert a pharmacological activity. The obstacle posed by the BBB has led to the in-depth study of strategies allowing the brain delivery of CNS-active drugs. Among the most promising strategies is the use of peptides addressed to the BBB. Peptides are versatile molecules that can be used to decorate nanoparticles or can be conjugated to drugs, with either a stable link or as pro-drugs. They have been used to deliver to the brain both small molecules and proteins, with applications in diverse therapeutic areas such as brain cancers, neurodegenerative diseases and imaging. Peptides can be generally classified as receptor-targeted, recognizing membrane proteins expressed by the BBB microvessels (e.g., Angiopep2, CDX, and iRGD), "cell-penetrating peptides" (CPPs; e.g. TAT_47-57, SynB1/3, and Penetratin), undergoing transcytosis through unspecific mechanisms, or those exploiting a mixed approach. The advantages of peptides have been extensively pointed out, but so far few studies have focused on the potential negative aspects. Indeed, despite having a generally good safety profile, some peptide conjugates may display toxicological characteristics distinct from those of the peptide itself, causing for instance antigenicity, cardiovascular alterations or hemolysis. Other shortcomings are the often brief lifetime in vivo, caused by the presence of peptidases, the vulnerability to endosomal/lysosomal degradation, and the frequently still insufficient attainable increase of brain drug levels, which remain below the therapeutically useful concentrations. The aim of this review is to analyze not only the successful and promising aspects of the use of peptides in brain targeting but also the problems posed by this strategy for drug delivery.

Physicochemical Characterization of Hyaluronic Acid and Chitosan Liposome Coatings

Hyaluronic acid (HA) and chitosan (CH) are biopolymers that are widely used in many biomedical applications and for cosmetic purposes. Their chemical properties are fundamental to them working as drug delivery systems and improving their synergistic effects. In this work, two different protocols were used to obtain zwitterionic liposomes coated with either hyaluronic acid or chitosan. Specifically, the methodologies used to perform vesicle preparation were chosen by taking into account the specific chemical properties of these two polysaccharides. In the case of chitosan, liposomes were first synthesized and then coated, whereas the coating of hyaluronic acid was achieved through lipidic film hydration in an HA aqueous solution. The size and the zeta-potential of the polysaccharide-coated liposomes were determined by dynamic light scattering (DLS). This approach allowed coated liposomes to be obtained with hydrodynamic diameters of 264.4 ± 12.5 and 450.3 ± 16.7 nm for HA- and CH-coated liposomes, respectively. The chemical characterization of the coated liposomal systems was obtained by surface infrared (ATR-FTIR) and nuclear magnetic resonance (NMR) spectroscopies. In particular, the presence of polysaccharides was confirmed by the bands assigned to amides and saccharides being in the 1500–1700 cm−1 and 800–1100 cm−1 regions, respectively. This approach allowed confirmation of the efficiency of the coating processes, evidencing the presence of HA or CH at the liposomal surface. These data were also supported by time-of-flight secondary ion mass spectrometry (ToF-SIMS), which provided specific assessments of surface (3–5 nm deep) composition and structure of the polysaccharide-coated liposomes. In this work, the synthesis and the physical chemistry characterization of coated liposomes with HA or CH represent an important step in improving the pharmacological properties of drug delivery systems.

In silico and in vitro design of cordycepin encapsulation in liposomes for colon cancer treatment

Cordycepin or 3'-deoxyadenosine is an interesting anti-cancer drug candidate that is found in abundance in the fungus Cordyceps militaris. It inhibits cellular growth of many cancers including lung carcinoma, melanoma, bladder cancer, and colon cancer by inducing apoptosis, anti-proliferation, anti-metastasis and by arresting the cell cycle. Cordycepin has, however, poor stability and low solubility in water, resulting in loss of its bioactivity. Liposomes can be used to overcome these obstacles. Our aim is to improve cordycepin's anti-colon cancer activity by liposome encapsulation. Cordycepin-encapsulated liposomes were designed and fabricated based on a combination of theoretical and experimental studies. Molecular dynamics (MD) simulations and free energy calculations suggest that phosphatidylcholine (PC) lipid environment is favorable for cordycepin adsorption. Cordycepin passively permeates into PC lipid bilayers without membrane damage and strongly binds to the lipids' polar groups by flipping its deoxyribose sugar toward the bilayer center. Our fabricated liposomes containing 10 : 1 molar ratio of egg yolk PC : cholesterol showed encapsulation efficiency (%EE) of 99% using microfluidic hydrodynamic focusing (MHF) methods. In our in vitro study using the HT-29 colon cancer cell line, cordycepin was able to inhibit growth by induction of apoptosis. Cell viability was significantly decreased below 50% at 125 μg mL-1 dosage after 48 h treatment with non-encapsulated and encapsulated cordycepin. Importantly, encapsulation provided (1) a 2-fold improvement in the inhibition of cancer cell growth at 125 μg mL-1 dosage and (2) 4-fold increase in release time. These in silico and in vitro studies indicate that cordycepin-encapsulated liposomes could be a potent drug candidate for colon cancer therapy.

Sorting hidden patterns in nanoparticle performance for glioblastoma using machine learning algorithms

Cationic compounds have been described to readily penetrate cell membranes. Assigning positive charge to nanosystems, e.g. lipid nanoparticles, has been identified as a key feature to promote electrostatic binding and design ligand-based constructs for tumour targeting. However, their intrinsic high cytotoxicity has hampered their biomedical application. This paper seeks to establish which cationic compounds and properties are compelling for interface modulation, in order to improve the design of tumour targeted nanoparticles against glioblastoma. How can intrinsic features (e.g. nature, structure, conformation) shape efficacy outcomes? In the quest for safer alternative cationic compounds, we evaluate the effects of two novel glycerol-based lipids, GLY1 and GLY2, on the architecture and performance of nanostructured lipid carriers (NLCs). These two molecules, composed of two alkylated chains and a glycerol backbone, differ only in their polar head and proved to be efficient in reversing the zeta potential of the nanosystems to positive values. The use of unsupervised and supervised machine learning (ML) techniques unraveled their structural similarities: in spite of their common backbone, GLY1 exhibited a better performance in increasing zeta potential and cytotoxicity, while decreasing particle size. Furthermore, NLCs containing GLY1 showed a favorable hemocompatible profile, as well as an improved uptake by tumour cells. Summing-up, GLY1 circumvents the intrinsic cytotoxicity of a common surfactant, CTAB, is effective at increasing glioblastoma uptake, and exhibits encouraging anticancer activity. Moreover, the use of ML is strongly incited for formulation design and optimization.

Peptide-lipid nanoconstructs act site-specifically towards glioblastoma growth impairment

Ultra-small nanostructured lipid carriers (usNLCs) have been hypothesized to promote site-specific glioblastoma (GB) drug delivery. Envisioning a multitarget purpose towards tumor cells and microenvironment, a surface-bioconjugated usNLC prototype is herein presented. The comeback of co-delivery by repurposing atorvastatin and curcumin, as complementary therapy, was unveiled and characterized, considering colloidal properties, stability, and drug release behavior. Specifically, the impact of the surface modification of usNLCs with hyaluronic acid (HA) conjugates bearing the cRGDfK and H₇k(R₂)₂ peptides, and folic acid (FA) on GB cells was sequentially evaluated, in terms of cytotoxicity, internalization, uptake mechanism and hemolytic character. As proof-of-principle, the biodistribution, tolerability, and efficacy of the nanocarriers were assessed, the latter in GB-bearing mice through magnetic resonance imaging and spectroscopy. The hierarchical modification of the usNLCs promotes a preferential targeting behavior to the brain, while simultaneously sparing the elimination by clearance organs. Moreover, usNLCs were found to be well tolerated by mice and able to impair tumor growth in an orthotopic xenograft model, whereas for mice administered with the non-encapsulated therapeutic compounds, tumor growth exceeded 181% in the same period. Relevant biomarkers extracted from metabolic spectroscopy were ultimately identified as a potential tumor signature.