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      Modification approaches of plant-based proteins to improve their techno-functionality and use in food products

      , ,
      Food Hydrocolloids
      Elsevier BV

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          Reducing food’s environmental impacts through producers and consumers

          Food's environmental impacts are created by millions of diverse producers. To identify solutions that are effective under this heterogeneity, we consolidated data covering five environmental indicators; 38,700 farms; and 1600 processors, packaging types, and retailers. Impact can vary 50-fold among producers of the same product, creating substantial mitigation opportunities. However, mitigation is complicated by trade-offs, multiple ways for producers to achieve low impacts, and interactions throughout the supply chain. Producers have limits on how far they can reduce impacts. Most strikingly, impacts of the lowest-impact animal products typically exceed those of vegetable substitutes, providing new evidence for the importance of dietary change. Cumulatively, our findings support an approach where producers monitor their own impacts, flexibly meet environmental targets by choosing from multiple practices, and communicate their impacts to consumers.
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            Self-assembling peptide and protein amyloids: from structure to tailored function in nanotechnology.

            Self-assembled peptide and protein amyloid nanostructures have traditionally been considered only as pathological aggregates implicated in human neurodegenerative diseases. In more recent times, these nanostructures have found interesting applications as advanced materials in biomedicine, tissue engineering, renewable energy, environmental science, nanotechnology and material science, to name only a few fields. In all these applications, the final function depends on: (i) the specific mechanisms of protein aggregation, (ii) the hierarchical structure of the protein and peptide amyloids from the atomistic to mesoscopic length scales and (iii) the physical properties of the amyloids in the context of their surrounding environment (biological or artificial). In this review, we will discuss recent progress made in the field of functional and artificial amyloids and highlight connections between protein/peptide folding, unfolding and aggregation mechanisms, with the resulting amyloid structure and functionality. We also highlight current advances in the design and synthesis of amyloid-based biological and functional materials and identify new potential fields in which amyloid-based structures promise new breakthroughs.
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              Amyloid Fibrils as Building Blocks for Natural and Artificial Functional Materials.

              Proteinaceous materials based on the amyloid core structure have recently been discovered at the origin of biological functionality in a remarkably diverse set of roles, and attention is increasingly turning towards such structures as the basis of artificial self-assembling materials. These roles contrast markedly with the original picture of amyloid fibrils as inherently pathological structures. Here we outline the salient features of this class of functional materials, both in the context of the functional roles that have been revealed for amyloid fibrils in nature, as well as in relation to their potential as artificial materials. We discuss how amyloid materials exemplify the emergence of function from protein self-assembly at multiple length scales. We focus on the connections between mesoscale structure and material function, and demonstrate how the natural examples of functional amyloids illuminate the potential applications for future artificial protein based materials.

                Author and article information

                Contributors
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                Journal
                Food Hydrocolloids
                Food Hydrocolloids
                Elsevier BV
                0268005X
                September 2021
                September 2021
                : 118
                : 106789
                Article
                10.1016/j.foodhyd.2021.106789
                81ad861f-ba23-4c75-bc59-015c1345f7f5
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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