Polyelectrolyte Precipitation: A New Green Chemistry Approach to Recover Value-Added Proteins from Different Sources in a Circular Economy Context.
Ricardo Gómez-GarcíaAna A Vilas-BoasAna Martins Vilas-BoasDébora A CamposManuela PintadoPublished in: Molecules (Basel, Switzerland) (2022)
Proteins have always been vital biological molecules used for industrial purposes, human nutrition and health. Nowadays, seeking new alternatives and sources of these biomolecules is becoming an increasing research trend derived from the present consumer awareness between food consumption and health promotion, but also on environmental sustainability. Although there are different consolidated/traditional downstream processes to obtain proteins, such as chromatography tools, alkali hydrolysis, precipitation by inorganic salts and organic solvents, their industrial-scale application still demands urgent innovation due to the poor recovery yields, high costs and time-consuming steps, environmental impact as well as some toxic concerns. Polyelectrolyte precipitation represents a green, innovative alternative for protein recovery; however, there are reduced data regarding its pilot or industrial-scale application. In this literature work, the action mechanism and principles with regards to its functionality and insights for its application on a big scale are reviewed. Overall, this review discusses the novelty and sustainability of protein precipitation by polyelectrolytes from different sources against traditional techniques as well as highlights the relationship between protein source, production relevance and bioactive properties that are key factors to maximize the application of this extractive method on a circular economy context.
Keyphrases
- health promotion
- heavy metals
- drinking water
- wastewater treatment
- protein protein
- human health
- mental health
- endothelial cells
- life cycle
- healthcare
- big data
- amino acid
- systematic review
- binding protein
- public health
- physical activity
- health information
- risk assessment
- randomized controlled trial
- clinical trial
- electronic health record
- deep learning
- machine learning
- high performance liquid chromatography
- social media
- tandem mass spectrometry