COVER STORY: ASHLAND
datasets to detect concealed patterns and draw predictions that only the machine can discern. Bioinformatics can use AI approaches to explore structural chemistry and biology, genomics, proteomics, and pharmacologic data to predict potential interactions between phytocomponents and proteins and the possible modulation of gene expression and signaling pathways. This approach is identified as “network pharmacology”, a term introduced in 2007 by Andrew L. Hopkins.
Systems pharmacology study of Sandalwood extract in silico The analytical determination of SW has led to the identification of seventeen key phytocomponents with potential biological activity. Network pharmacology analysis was used to predict the potential skin biological activity (Fig 1). First, a compound-target network was established via virtual screening based on similarity structure prediction combined with literature and database mining. Second, the curated compound-target network resulting in a total of 482 genes, served as a base to gene and pathway enrichment studies. This led to the identification of 2803 biological processes, 348 molecular functions and 267 cellular components, that were further refined to focus on a subset of 125 skin-related genes that served as a basis for skin biological activity prediction. The workflow of the study is presented in Figure 1. Predicted skin biological activities (Figure
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regulation, and hair growth and folliculogenesis. These predicted areas and the related genes constitute a pool of potential biological activities that can be further validated experimentally.
Experimental validation of the biological activity of Sandalwood extract in vitro Part of the study of the biological activity of SW in vitro was undertaken on skin models to delineate the potential role of OR2AT4 in skin homeostasis. The topical application of 1% and 2% SW extract on normal human skin biopsies showed an increase in OR2AT4 content after 48
hours (+17% and +21%, respectively). The reconstruction of epidermal equivalents
Figure 2: Skin-related network of predicted compound-target-skin biological activity relationships. The seventeen phytocompounds are numbered (1 to 17). Selected predicted biological activity is shown.
2) comprised: anti-ageing (including senolytic activity, telomere protection, extracellular matrix organisation), regulation of inflammation, response to various stresses, skin olfactory receptor modulation, skin barrier homeostasis (epidermal development and regeneration, cell- to-cell junctions), mitochondrial homeostasis, DNA repair, antioxidant defenses, sebum
with the keratinocytes isolated from donors of various age suggested that OR2AT4 expression was decreased with age (Fig 3). This observation pointed out OR2AT4 as a sensory receptor that decreased with age and hence can be considered as a marker to evaluate the olfactory signature of ageing in vitro. Next, experiments were conducted in order
to determine if epidermal OR2AT4 could be modulated following the exposition to external stress such as the application of volatile organic compounds (VOCs) from car exhaust, in an epidermal reconstructed model to mimic the consequences of external stressors associated with extrinsic ageing. An overnight application of VOCs on reconstructed human epidermis was associated with a decrease of OR2AT4 (-33%) observed 48 hours after VOCs application. When SW extract was applied post VOCs application for 48 hours, the return to the basal OR2AT4 content was observed. A reconstructed epidermal model mimicking
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intrinsic ageing was also used to study the expression of OR2AT4 in this context of a senescent epidermis and the modulatory effect of SW extract (Figure 4). When compared with normal reconstructed
100 98 94 81 52 3yo 15yo 39yo 45yo 64yo
Figure 3. Immunodetection of OR2AT4 in human reconstructed epidermis obtained with keratinocytes from donors of increasing age.
epidermis, the reconstructed senescent epidermal model exhibited a lower OR2AT4 expression (-19 to -30%, according to the experiment). The topical application of 1% and 2% SW extract on reconstructed senescent epidermal model showed an increase in OR2AT4 content after 48 hours (+46% and +96%, compared to respective controls).
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+46% ***
-19% ***
-30% ***
+96% ***
Conclusion Inspired by wood therapy, SW, the trade name of which is Santalwood™ biofunctional, reduces the skin olfactory signature of ageing. It has clinically proven benefits on skin regeneration, firmness and wrinkles. Additionally, the bioinformatic network analysis of Santalwood™ revealed concealed skin biological pathways providing Santalwood™ with possible additional skin benefits and new horizons in future beauty products.
PC
normal RHE
senescent RHE
senescent RHE+1%
senescent RHE
senescent RHE+2%
*** highly significant with Student’s t test, n=6
Figure 4: Reconstructed senescent epidermal model showed a decreased expression of OR2AT4, that could be reversed by SW topical application for 48 hours.
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OR2AT4 relative expression (%)
OR2AT4 relative expression (%)
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