Fucoxanthin's Optimization from Undaria pinnatifida Using Conventional Heat Extraction, Bioactivity Assays and In Silico Studies.
Catarina Lourenço-LopesMaria Fraga-CorralAnton Soria-LopezBernabe Nuñes-EstevezMarta BarralAurora SilvaNingyang LiChao LiuBernabé Nuñez-EstevezMiguel Angel PrietoPublished in: Antioxidants (Basel, Switzerland) (2022)
Brown macroalgae are a potential source of natural pigments. Among them, Undaria pinnatifida is recognized for its high concentration of fucoxanthin (Fx), which is a pigment with a wide range of bioactivities. In this study, three independent parameters were optimized for conventional heat extraction (CHE) to maximize the recovery of Fx from Undaria pinnatifida . Optimal conditions ( temperature = 45 °C, solvent = 70%, and time = 61 min) extracted 5.1 mg Fx/g dw. Later, the bioactivities of the Fx-rich extracts (antioxidant, antimicrobial, and neuroprotective) were assessed using in vitro and in silico approaches. In vitro assays indicated that Fx has a strong antioxidant capacity and even stronger antimicrobial activity against gram-positive bacteria. This data was supported in silico where Fx established a high binding affinity to DR, a Staphylococcus aureus protein, through aa ALA-8, LEU-21, and other alkane interactions. Finally, the in vitro enzymatic inhibition of AChE using Fx, was further supported using docking models that displayed Fx as having a high affinity for aa TYR72 and THR 75; therefore, the Fx extraction behavior explored in this work may reduce the costs associated with energy and solvent consumption. Moreover, this paper demonstrates the efficiency of CHE when recovering high amounts of Fx from Undaria pinnatifida . Furthermore, these findings can be applied in different industries.
Keyphrases
- staphylococcus aureus
- molecular docking
- high throughput
- machine learning
- ionic liquid
- heat stress
- risk assessment
- escherichia coli
- nitric oxide
- hydrogen peroxide
- molecular dynamics simulations
- deep learning
- cystic fibrosis
- subarachnoid hemorrhage
- mass spectrometry
- big data
- single cell
- artificial intelligence
- solar cells
- human health