Multivariate Analysis Revealed Ultrasonic-Assisted Extraction Improves Anti-Melanoma Activity of Non-Flavonoid Compounds in Indonesian Brown Algae Ethanol Extract

In Vitro Anti-Oxidant, In Vivo Anti-Hyperglycemic, and Untargeted Metabolomics-Aided-In Silico Screening of Macroalgae Lipophilic Extracts for Anti-Diabetes Mellitus and Anti-COVID-19 Potential Metabolites

COVID-19 patients with comorbid DM face more severe outcomes, indicating that hyperglycemic conditions exacerbate SARS-CoV-2 infection. Negative side effects from existing hyperglycemia treatments have urged the need for safer compounds. Therefore, sourcing potential compounds from marine resources becomes a new potential approach. Algal lipids are known to possess beneficial activities for human health. However, due to limitations in analyzing large amounts of potential anti-hyperglycemic and anti-COVID-19-related marine metabolites, there is an increasing need for new approaches to reduce risks and costs. Therefore, the main aim of this study was to identify potential compounds in macroalgae Sargassum cristaefolium, Tricleocarpa cylindrica, and Ulva lactuca lipophilic extracts for treating DM and COVID-19 by an integrated approach utilizing in vitro anti-oxidant, in vivo anti-hyperglycemic, and metabolomic-integrated in silico approaches. Among them, S. cristaefolium and T. cylindrica showed potential anti-hyperglycemic activity, with S. cristaefolium showing the highest anti-oxidant activity. A GC-MS-based untargeted metabolomic analysis was used to profile the lipophilic compounds in the extracts followed by an in silico molecular docking analysis to examine the binding affinity of the compounds to anti-DM and anti-COVID-19 targets, e.g., α-amylase, α-glucosidase, ACE2, and TMPRSS2. Notably, this study reveals for the first time that steroid-derived compounds in the macroalgae T. cylindrica had higher binding activity than known ligands for all the targets mentioned. Studies on drug likeliness indicate that these compounds possess favorable drug properties. These findings suggest the potential for these compounds to be further developed to treat COVID-19 patients with comorbid DM. The information in this study would be a basis for further in vitro and in vivo analysis. It would also be useful for the development of these candidate compounds into drug formulations.

Enhanced Expression of p53 and Suppression of PI3K/Akt/mTOR by Three Red Sea Algal Extracts: Insights on Their Composition by LC-MS-Based Metabolic Profiling and Molecular Networking

Brown algae comprise up to 2000 species with wide dissemination in temperate zones. A comprehensive untargeted metabolic profiling guided by molecular networking of three uninvestigated Red-Sea-derived brown algae, namely Sirophysalis trinodis, Polycladia myrica, and Turbinaria triquetra, led to the identification of over 115 metabolites categorized as glycerolipids, fatty acids, sterol lipids, sphingolipids, and phospholipids. The three algae exhibited low-to-moderate antioxidant capacity using DPPH and ABTS assays. Preliminary in vitro antiproliferative studies showed that the algal extracts displayed high cytotoxic activity against a panel of cancer cell lines. The most potent activity was recorded against MCF-7 with IC₅₀ values of 51.37 ± 1.19, 63.44 ± 1.13, and 59.70 ± 1.22 µg/mL for S. trinodis, P. myrica, and T. triquetra, respectively. The cytotoxicity of the algae was selective to MCF-7 without showing notable effects on the proliferation of normal human WISH cells. Morphological studies revealed that the algae caused cell shrinkage, increased cellular debris, triggered detachment, cell rounding, and cytoplasmic condensation in MCF-7 cancer cells. Mechanistic investigations using flow cytometry, qPCR, and Western blot showed that the algae induced apoptosis, initiated cell cycle arrest in the sub-G₀/G₁ phase, and inhibited the proliferation of cancer cells via increasing mRNA and protein expression of p53, while reducing the expression of PI3K, Akt, and mTOR.

Network pharmacology integrated with experimental validation revealed potential molecular mechanisms of Camellia nitidissima C. W. Chi in the treatment of lung cancer

ETHNOPHARMACOLOGICAL RELEVANCE

Camellia nitidissima C.W.Chi (CNC), an ethnomedicine mainly distributed in Southern China's Guangxi Zhuang Autonomous Region, is known as "Panda in plants" and "Camellias Queen" due to its golden blossom. CNC has been applied as a traditional folk medicine in cancer therapy.

AIM OF THE STUDY

This study utilized network pharmacology analysis combined with experimental validation to identify the substance basis and potential molecular mechanism of CNC against lung cancer.

MATERIALS AND METHODS

The active ingredients of CNC were identified based on published literature. The associated potential targets of CNC in lung cancer treatment were predicted using integrated network pharmacology analysis and molecular docking. The underlying molecular mechanism of CNC in lung cancer were validated in human lung cancer cell lines.

RESULTS

A total of 30 active ingredients and 53 targets of CNC were screened. An enrichment analysis of Gene Ontology (GO) revealed that the effects of CNC in lung cancer mainly involve protein binding, regulation of cell proliferation and apoptosis, and signal transduction. KEGG pathways analysis suggested that CNC might exert cancer suppression effects mainly through pathways in cancer, PI3K/AKT signaling pathway. Molecular docking revealed that CNC has high affinity for binding of EGFR, SRC, AKT1, and CCND1 to the key active ingredients including luteolin, kaempferol, quercetin, eriodictyol and 3'4-O-dimethylcedrusin. In in vitro experiments, CNC played the inhibitory roles in lung cancer cells by inducing cell apoptosis, causing G0/G1 and S cell cycle arrest, increasing intracellular ROS levels, and promoting the apoptotic proteins Bax and Caspase-3. Meanwhile, CNC also regulated the expression of core proteins EGFR, SRC, and AKT.

CONCLUSION

These results comprehensively clarified the associated substance basis and underlying molecular mechanism of CNC against lung cancer, which would be contributed to develop promising anti-cancer pharmaceuticals or therapeutic approaches for lung cancer therapy.

Antioxidant, Tyrosinase, α-Glucosidase, and Elastase Enzyme Inhibition Activities of Optimized Unripe Ajwa Date Pulp (Phoenix dactylifera) Extracts by Response Surface Methodology

The Ajwa date (Phoenix dactylifera L., Arecaceae family) is a popular edible fruit consumed all over the world. The profiling of the polyphenolic compounds of optimized unripe Ajwa date pulp (URADP) extracts is scarce. The aim of this study was to extract polyphenols from URADP as effectively as possible by using response surface methodology (RSM). A central composite design (CCD) was used to optimize the extraction conditions with respect to ethanol concentration, extraction time, and temperature and to achieve the maximum amount of polyphenolic compounds. High-resolution mass spectrometry was used to identify the URADP's polyphenolic compounds. The DPPH-, ABTS-radical scavenging, α-glucosidase, elastase and tyrosinase enzyme inhibition of optimized extracts of URADP was also evaluated. According to RSM, the highest amounts of TPC (24.25 ± 1.02 mgGAE/g) and TFC (23.98 ± 0.65 mgCAE/g) were obtained at 52% ethanol, 81 min time, and 63 °C. Seventy (70) secondary metabolites, including phenolic, flavonoids, fatty acids, and sugar, were discovered using high-resolution mass spectrometry. In addition, twelve (12) new phytoconstituents were identified for the first time in this plant. Optimized URADP extract showed inhibition of DPPH-radical (IC₅₀ = 87.56 mg/mL), ABTS-radical (IC₅₀ = 172.36 mg/mL), α-glucosidase (IC₅₀ = 221.59 mg/mL), elastase (IC₅₀ = 372.25 mg/mL) and tyrosinase (IC₅₀ = 59.53 mg/mL) enzymes. The results revealed a significant amount of phytoconstituents, making it an excellent contender for the pharmaceutical and food industries.