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. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 11 is March 25, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

中文翻译：

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理解和控制食物中的蛋白质结构和功能：从实验和计算机模拟的角度。

蛋白质的结构和相互作用在决定许多食品、饮料和药品的质量属性方面起着至关重要的作用。结合对蛋白质结构-功能关系的多尺度理解，可以更深入地了解和控制相关过程。通过机器学习将来自实验测量、人类感官面板和计算机模拟的数据相结合，可以构建将蛋白质的纳米级特性与物理化学特性、生理结果和食物味道相关联的统计模型。这篇综述重点介绍了分子、中尺度和多尺度水平的高级计算机模拟的几个例子，它们阐明了食品中的作用机制，从而促进了它们的控制。它包括一个实用的仿真工具箱，适用于计算机建模新手。《食品科学与技术年度评论》第 11 卷的预计最终在线出版日期为 2020 年 3 月 25 日。请参阅 http://www.annualreviews.org/page/journal/pubdates 了解修订后的估计值。