Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design

Design, Synthesis, and Biological Evaluation of New Azulene-Containing Chalcones

Azulene-containing chalcones have been synthesized via Claisen-Schmidt condensation reaction. Their chemical structure has been established by spectroscopic methods where the ¹H-NMR spectra suggested that the title chalcones were geometrically pure and configured trans (J = 15 Hz). The influence of functional groups from azulene-containing chalcones on the biological activity of the 2-propen-1-one unit was investigated for the first time. This study presents optical and fluorescent investigations, QSAR studies, and biological activity of 10 novel compounds. These chalcones were evaluated for their antimicrobial activity against Gram-positive and Gram-negative bacteria. The results revealed that most of the synthesized compounds showed inhibition against Gram-negative microorganisms, independent of the substitution of azulene scaffold. Instead, all azulene-containing chalcones exhibited good antifungal activity against Candida parapsilosis, with MIC values ranging between 0.156 and 0.312 mg/mL. The most active compound was chalcone containing azulene moieties on both sides of the 2-propene-1-one bond, exhibiting good activity against both bacteria-type strains and good antifungal activity. This antifungal activity combined with low toxicity makes azulene-containing chalcones a new class of bioorganic compounds.

Multifunctional TiO2/SBA-15 mesoporous silica hybrids loaded with organic sunscreens for skin application: The role in photoprotection and pollutant adsorption with reduced sunscreen permeation

TiO₂ acts as an inorganic sunscreen and photocatalyst to protect humans from environmental pollutants. We incorporated TiO₂ into mesoporous silica (SBA-15) for skin application to prevent environmental stresses including UVA irradiation and pollutant invasion. Organic ultraviolet (UV)A filters such as avobenzone and oxybenzone were then loaded into mesoporous support for synergistic sunscreen efficiency. The as-prepared formulations with different TiO₂ amounts (10 %-50 %) were fabricated. The pore size decreased from 4.72 to 4.00 nm following the increase in TiO₂ percentage. TiO₂/SBA-15 captured about 60 % fluoranthene and 80 % furfural within 3 h with no significant difference due to different TiO₂ content. The in vitro photoprotection assessed by UVA/UVB ratio exhibited the increase in Boots star rating from 2 to 3 to 5 by entrapment of avobenzone into TiO₂/SBA-15. Thirty-percent TiO₂/SBA-15 in hydrogel decreased avobenzone and oxybenzone deposition by 70 % and 80 % compared to free form, respectively. Avobenzone and TiO₂ supplementation to SBA-15 significantly alleviated skin cell death and neutrophil recruitment in the photoaged mouse skin compared to the SBA-15 application alone. Compared to the UVA-irradiated skin, 30 % TiO₂/SBA-15 showed a 2.5- and 3.1-fold decline in IL-1β and IL-6 levels, respectively. The TiO₂/SBA-15 hybrid was considered non-irritant based on results of cytotoxicity assay, skin histology, and cutaneous barrier function. Our data indicate that the versatile mesoporous silica is an effective system for topical use in sunscreen and skin protection.

The absorption of polycyclic aromatic hydrocarbons into the skin to elicit cutaneous inflammation: The establishment of structure-permeation and in silico-in vitro-in vivo relationships

Polycyclic aromatic hydrocarbons (PAHs) can induce skin toxicity. Although some investigations have been conducted to assess the skin toxicity of different PAHs, few comparisons using a series of PAHs with different ring numbers and arrangements have been done. We aimed to explore the skin absorption of 6 PAH compounds and their effect on cutaneous inflammation. In vitro skin permeation was rated by Franz cell with pig skin. Molecular docking was employed to compute the PAH interaction with stratum corneum (SC) lipids. Cultured keratinocytes were exposed to PAHs for analyzing cytotoxicity, cyclooxygenase (COX)-2, prostaglandin E₂ (PGE₂), chemokines, and differentiation proteins. The in vivo topical PAH exposure in mice was characterized by skin absorption, transepidermal water loss (TEWL), PGE₂ level, and histology. The skin deposition from the aqueous vehicle increased following the increase of PAH lipophilicity and molecular size, with benzo[a]pyrene (5-ring PAH) showing the greatest absorption. Pyrene was the compound showing the highest penetration across the skin (flux). Although the PAHs fluoranthene, pyrene, chrysene, and 1,2-benzanthracene all had 4 rings, the skin permeation was quite different. 1,2-Benzanthracene showed the greatest absorption among the 4-ring compounds. The PAHs with higher absorption exhibited stronger interaction with SC lipids according to the in silico modeling. Chrysene and 1,2-benzanthracene generally showed the highest COX-2 and PGE₂ expression, followed by benzo[a]pyrene. The lowest COX-2 and PGE₂ upregulation was observed for naphthalene (2-ring PAH). A contrary tendency was detected for the upregulation of chemokines. Filaggrin and integrin β1 in keratinocytes were suppressed at a comparable level by all PAHs. The skin's absorption of PAHs showed strong in vivo-in vitro correlation. 1,2-Benzanthracene and benzo[a]pyrene highly disrupted the skin barrier and elevated the inflammation in vivo. The tendency toward in vivo inflammation caused by various PAHs could be well predicted by the combined estimation using in vitro skin absorption and a keratinocyte bioassay. This study also established the structure-permeation relationship (SPR) of PAHs.

Mathematical models for dermal drug absorption

INTRODUCTION

Mathematical models of dermal transport offer the advantages of being much faster and less expensive than in vitro or in vivo studies. The number of methods used to create such models has been increasing rapidly, probably due to the steady rise in computational power. Although each of the various approaches has its own virtues and limitations, it may be difficult to decide which approach is best suited to address a given problem.

AREAS COVERED

Here we outline the basic ideas, drawbacks and advantages of compartmental and quantitative structure-activity relationship models, as well as of analytical and numerical approaches for solving the diffusion equation. Examples of special applications of the different approaches are given.

EXPERT OPINION

Although some models are sophisticated and might be used in future to predict transport through damaged or diseased skin, the comparatively low availability of suitable and accurate experimental data limits extensive usage of these models and their predictive accuracy. Due to the lack of experimental data, the possibility of validating mathematical models is limited.

Predicting skin permeability from complex chemical mixtures: incorporation of an expanded QSAR model

Quantitative structure-activity relationship (QSAR) models have been widely used to study the permeability of chemicals or solutes through skin. Among the various QSAR models, Abraham's linear free-energy relationship (LFER) model is often employed. However, when the experimental conditions are complex, it is not always appropriate to use Abraham's LFER model with a single set of regression coefficients. In this paper, we propose an expanded model in which one set of partial slopes is defined for each experimental condition, where conditions are defined according to solvent: water, synthetic oil, semi-synthetic oil, or soluble oil. This model not only accounts for experimental conditions but also improves the ability to conduct rigorous hypothesis testing. To more adequately evaluate the predictive power of the QSAR model, we modified the usual leave-one-out internal validation strategy to employ a leave-one-solute-out strategy and accordingly adjust the Q(2) LOO statistic. Skin permeability was shown to have the rank order: water > synthetic > semi-synthetic > soluble oil. In addition, fitted relationships between permeability and solute characteristics differ according to solvents. We demonstrated that the expanded model (r(2) = 0.70) improved both the model fit and the predictive power when compared with the simple model (r(2) = 0.21).