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Understanding and Controlling Food Protein Structure and Function in Foods: Perspectives from Experiments and Computer Simulations.


ABSTRACT: The structure and interactions of proteins play a critical role in determining the quality attributes of many foods, beverages, and pharmaceutical products. Incorporating a multiscale understanding of the structure-function relationships of proteins can provide greater insight into, and control of, the relevant processes at play. Combining data from experimental measurements, human sensory panels, and computer simulations through machine learning allows the construction of statistical models relating nanoscale properties of proteins to the physicochemical properties, physiological outcomes, and tastes of foods. This review highlights several examples of advanced computer simulations at molecular, mesoscale, and multiscale levels that shed light on the mechanisms at play in foods, thereby facilitating their control. It includes a practical simulation toolbox for those new to in silico modeling.

SUBMITTER: Barroso da Silva FL 

PROVIDER: S-EPMC7379328 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Understanding and Controlling Food Protein Structure and Function in Foods: Perspectives from Experiments and Computer Simulations.

Barroso da Silva Fernando Luís FL   Carloni Paolo P   Cheung David D   Cottone Grazia G   Donnini Serena S   Foegeding E Allen EA   Gulzar Muhammad M   Jacquier Jean Christophe JC   Lobaskin Vladimir V   MacKernan Donal D   Mohammad Hosseini Naveh Zeynab Z   Radhakrishnan Ravi R   Santiso Erik E EE  

Annual review of food science and technology 20200117


The structure and interactions of proteins play a critical role in determining the quality attributes of many foods, beverages, and pharmaceutical products. Incorporating a multiscale understanding of the structure-function relationships of proteins can provide greater insight into, and control of, the relevant processes at play. Combining data from experimental measurements, human sensory panels, and computer simulations through machine learning allows the construction of statistical models rel  ...[more]

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