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

Fernando Luís Barroso da Silva¹, Paolo Carloni^2,3, David Cheung⁴

¹School of Pharmaceutical Sciences at Ribeirão Preto, University of São Paulo, BR-14040-903, Ribeirão Preto, São Paulo, Brazil.

Annual Review of Food Science and Technology

|January 18, 2020

Summary

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This summary is machine-generated.

Understanding protein structure-function relationships using multiscale computer simulations and machine learning offers greater control over food and pharmaceutical quality. This approach links nanoscale protein properties to sensory and physicochemical attributes.

Area of Science:

Food science
Biophysics
Computational chemistry

Background:

Protein structure and interactions are crucial for food, beverage, and pharmaceutical quality.
A multiscale understanding of protein structure-function relationships is needed for process control.

Purpose of the Study:

To review advanced computer simulations for understanding protein mechanisms in foods.
To provide a practical guide to in silico modeling for controlling food properties.

Main Methods:

Combining experimental data, sensory panel results, and computer simulations.
Utilizing machine learning to build statistical models.
Employing molecular, mesoscale, and multiscale simulation techniques.

Main Results:

Keywords:

GPCR QSAR coarse graining constant-pH simulation molecular dynamics molecular interactions rare-event methods

Related Experiment Videos

Developed models linking nanoscale protein properties to food physicochemical properties and taste.
Demonstrated how advanced simulations elucidate mechanisms in food systems.
Provided insights into controlling food quality through protein manipulation.

Conclusions:

Multiscale modeling of protein structure-function relationships enhances control over food and pharmaceutical product quality.
In silico tools offer practical approaches for optimizing food processing and product development.