Correlation between the structure and skin permeability of compounds

Antibacterial and Cytotoxicity of Extracts and Isolated Compounds from Artemisia abyssinica: A Combined Experimental and Computational Study

Artemisia abyssinica is a widely cultivated hedge plant in Ethiopia. Traditionally, they have been used to treat a variety of health conditions, including intestinal problems, infectious diseases, tonsillitis, and leishmaniasis. Silica gel chromatographic separation of the methanol and ethyl acetate extracts of the leaves, roots, and stem barks of A. abyssinica led to the isolation of 12 compounds, labeled as 1-12. Among these, compounds 1, 3, 4, 5, and 7-11 are reported as new to the genus Artemisia. The extracts and isolated compounds from A. abyssinica were evaluated for their in vitro antibacterial activity against four bacterial strains: Streptococcus pyogenes, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli, using the disc diffusion assay. All of the extracts displayed weak antibacterial activity, with inhibition zone diameters (IZDs) ranging from 6.10 ± 0.3 to 9.30 ± 0.20 mm. The isolated compounds, on the other hand, exhibited weak to moderate antibacterial activity, with IZDs ranging from 6.00 ± 0.300 to 13.50 ± 0.50 mm. The most potent antibacterial activity was observed for compound 6, which showed an IZD of 13.30 ± 0.50 mm against E. coli and 13.50 ± 0.50 mm against P. aeruginosa. This activity was comparable to that of the positive control ceftriaxone, which had IZDs of 14.1 ± 0.3 and 13.8 ± 0.5 mm against E. coli and P. aeruginosa, respectively. The in silico molecular docking analysis against DNA gyrase B revealed that compound 5 showed a higher binding affinity (-6.9 kcal/mol), followed by compound 10 (-6.7 kcal/mol) and compound 12 (-6.3 kcal/mol), whereas ciprofloxacin showed -7.3 kcal/mol. The binding affinities of compounds 5, 11, 10, and 9 were found to be -5.0, -4.3, -4.2, and -4.0 kcal/mol against S. aureus Pyruvate kinase, respectively, whereas ciprofloxacin showed a binding affinity of -4.9 kcal/mol, suggesting that compound 5 had a better binding affinity compared with ciprofloxacin. The effect of extracts of A. abyssinica was evaluated for cytotoxic activity against the breast cancer cell line (MCF-7) by the MTT assay. The extracts induced a decrease in cell viability and exerted a cytotoxic effect at a concentration of 20 μg/mL. The highest percent cell viability was observed for the methanol extract of the stem (92.9%), whereas the least was observed for the methanol extract of the root (34.5%). The result of the latter was significant compared with the positive control. The binding affinities of the isolated compounds were also assessed against human topoisomerase inhibitors IIβ. Results showed that compound 5 showed a binding affinity of -6.0 kcal/mol, followed by 11 (-5.4 kcal/mol), 10 (-5.0 kcal/mol), and 11 (-4.9 kcal/mol). Similar to ciprofloxacin, compounds 4, 5, 6, 9, 10, and 12 comply with Lipinski's rule of five. Overall, the comprehensive investigation of the chemical constituents and their biological activities reinforces the traditional medicinal applications of A. abyssinica and warrants further exploration of this plant as a source of novel therapeutic agents.

Development of a Mass Spectrometry Imaging Method to Evaluate the Penetration of Moisturizing Components Coated on Surgical Gloves into Artificial Membranes

Skin dryness and irritant contact dermatitis induced by the prolonged use of surgical gloves are issues faced by physicians. To address these concerns, manufacturers have introduced surgical gloves that incorporate a moisturizing component on their inner surface, resulting in documented results showing a reduction in hand dermatitis. However, the spatial distribution of moisturizers applied to surgical gloves within the integument remains unclear. Using matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI), we investigated the spatial distribution of moisturizers in surgical gloves within artificial membranes. Recently, dermal permeation assessments using three-dimensional models, silicone membranes, and Strat-M have gained attention as alternative approaches to animal testing. Therefore, in this study, we established an in vitro dermal permeation assessment of commercially available moisturizers in surgical gloves using artificial membranes. In this study, we offer a methodology to visualize the infiltration of moisturizers applied to surgical gloves into an artificial membrane using MALDI-MSI, while evaluating commercially available moisturizer-coated surgical gloves. Using our penetration evaluation method, we confirmed the infiltration of the moisturizers into the polyethersulfone 2 and polyolefin layers, which correspond to the epidermis and dermis of the skin, after the use of surgical gloves. The MSI-based method presented herein demonstrated the efficacy of evaluating the permeation of samples containing active ingredients.

In Silico Molecular Docking Analysis, Cytotoxicity, and Antibacterial Activities of Constituents of Fruits of Cucumis dipsaceus

Cucumis dipsaceus (Cucurbitaceae) is a plant traditionally used against diarrhea, teeth-ach, wounds, stomach ache, meningitis, and cancer. The extracts of C. dipsaceus after silica gel column chromatography gave nine compounds identified using spectroscopic methods such as hexacosane (1), octadecane (2), 17-(-5-ethyl-2,6-dihydroxy-6-methylhept-3-en-2-yl)-9-(hydroxymethyl)-13-methylcyclopenta[α]phenanthren-3-ol (3), erythrodiol (4), (9,12)-propyl icosa-9,12-dienoate (5), α-spinasterol (6), 16-dehydroxycucurbitacin (7), cucurbitacin D (8), and 23,24-dihydroisocucurbitacin D (9). Compounds 3 and 4 are new to the genus Cucumis. α-Spinasterol showed better inhibition zone diameter = 13.67 ± 0.57, 15.00 ± 0.10, and 13.33 ± 0.57 mm against Escherichia coli, Pseudomonas aeruginosa, and Streptococcus pyogenes compared with the other tested samples. α-Spinasterol (-8.0 kcal/mol) and 3 (-7.6 kcal/mol) displayed high binding affinity against DNA Gyrase compared to ciprofloxacin (-7.3 kcal/mol). α-Spinasterol and 16-dehydroxycucurbitacin showed better binding affinity against protein kinase. The cytotoxicity results revealed that the EtOAc extract showed the highest potency with IC50 = 16.05 μg/mL. 16-Dehydroxycucurbitacin showed a higher binding affinity (-7.7 kcal/mol) against human topoisomerase IIβ than etoposide. The cytotoxicity and antibacterial activities and in silico molecular docking analysis displayed by the constituents corroborate the traditional use of the plant against bacteria and cancer.

Semiquantitative sensitization safety assessment of extractable and leachables associated with parenteral pharmaceutical products

Extractable and leachables (E&Ls) associated with parenteral pharmaceutical products should be assessed for patient safety. One essential safety endpoint is local or systemic sensitization. However, there are no regulatory guidelines for quantitative sensitization safety assessment of E&Ls. A semiquantitative sensitization safety assessment workflow is developed to refine the sensitization safety assessment of E&Ls associated with parenteral pharmaceutical products. The workflow is composed of two sequential steps: local skin sensitization and systemic sensitization safety assessment. The local skin sensitization step has four tiers. The output from this step is the acceptable exposure level for local sensitization (AEL_ls) and this safety threshold can be used for local sensitization safety assessment. From the derived AEL_ls, the systemic sensitization safety assessment at step 2 proceeds in 2 tiers. The output from this workflow is the derivation of acceptable exposure level for systemic sensitization (AEL_ss). When the estimated human daily exposure (HDE) is compared with the AEL_ss, the margin of exposure is calculated to determine the sensitization safety of E&Ls following parenteral administration. The current work represents an initial effort to develop a scientifically robust process for sensitization safety assessment of E&Ls associated with parenteral pharmaceutical products.

Nutricosmetics: A new frontier in bioactive peptides' research toward skin aging

Food derived bioactive peptides are small protein fragments (2-20 amino acids long) that can exhibit health benefits, beyond basic nutrition. For example, food bioactive peptides can act as physiological modulators with hormone or drug-like activities including anti-inflammatory, antimicrobial, antioxidant, and the ability to inhibit enzymes related to chronic disease metabolism. Recently, bioactive peptides have been studied for their potential role as nutricosmetics. For example, bioactive peptides can impart skin-aging protection toward extrinsic (i.e., environmental and sun UV-ray damage) and intrinsic (i.e., natural cell or chronological aging) factors. Specifically, bioactive peptides have demonstrated antioxidant and antimicrobial activates toward reactive oxygen species (ROS) and pathogenic bacteria associated with skin diseases, respectively. The anti-inflammatory properties of bioactive peptides using in vivo models has also been reported, where peptides have shown to decreased the expression of IL-6, TNF-α, IL-1β, interferon-γ (INF-γ), and interleukin-17 (IL-17) in mice models. This chapter will discuss the main factors that trigger skin-aging processes, as well as provide examples of in vitro, in vivo, and in silico applications of bioactive peptides in relation to nutricosmetic applications.

Multifunctional Analysis of Chia Seed (Salvia hispanica L.) Bioactive Peptides Using Peptidomics and Molecular Dynamics Simulations Approaches

Chia seed peptides (CSP) can be a source of multifunctional biopeptides to treat non-communicable diseases. However, interactions and binding affinity involved in targeting specific receptors remains unexplored. In this study, molecular simulation techniques were used as virtual screening of CSP to determine drug-like candidates using a multi-target-directed ligand approach. CSP fraction with the best bioactivities in vitro was sequenced. Then, a prediction model was built using physicochemical descriptors (hydrophobicity, hydrophilicity, intestinal stability, antiangiogenic, antihypertensive, and anti-inflammatory) to calculate potential scores and rank possible biopeptides. Furthermore, molecular dynamics simulations (MDS) and ensemble molecular docking analysis were carried out using four human protein targets (ACE, angiotensin converting enzyme; VEGF, vascular endothelial growth factor; GLUC, glucocorticoid and MINC, mineralocorticoid receptors). Five known-sequence peptides (NNVFYPF, FNIVFPG, SRPWPIDY, QLQRWFR, GSRFDWTR) and five de novo peptides (DFKF, DLRF, FKAF, FRSF, QFRF) had the lowest energy score and higher affinity for ACE and VEGF. The therapeutic effects of these selected peptides can be related to the inhibition of the enzymes involved in angiogenesis and hypertension, due to formation of stable complexes with VEGF and ACE binding sites, respectively. The application of MDS is a good resource for identifying bioactive peptides for future experimental validation.

In Silico Prediction of Skin Permeability Using a Two-QSAR Approach

Topical and transdermal drug delivery is an effective, safe, and preferred route of drug administration. As such, skin permeability is one of the critical parameters that should be taken into consideration in the process of drug discovery and development. The ex vivo human skin model is considered as the best surrogate to evaluate in vivo skin permeability. This investigation adopted a novel two-QSAR scheme by collectively incorporating machine learning-based hierarchical support vector regression (HSVR) and classical partial least square (PLS) to predict the skin permeability coefficient and to uncover the intrinsic permeation mechanism, respectively, based on ex vivo excised human skin permeability data compiled from the literature. The derived HSVR model functioned better than PLS as represented by the predictive performance in the training set, test set, and outlier set in addition to various statistical estimations. HSVR also delivered consistent performance upon the application of a mock test, which purposely mimicked the real challenges. PLS, contrarily, uncovered the interpretable relevance between selected descriptors and skin permeability. Thus, the synergy between interpretable PLS and predictive HSVR models can be of great use for facilitating drug discovery and development by predicting skin permeability.