Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning.

IF 5.6 2区化学 Q1 CHEMISTRY, MEDICINAL

Journal of Chemical Information and Modeling Pub Date : 2024-07-22 Epub Date: 2024-07-01 DOI:10.1021/acs.jcim.4c00061

Nanako Inoue, Tomokazu Shibata, Yusuke Tanaka, Hiromu Taguchi, Ryusuke Sawada, Kenshin Goto, Shogo Momokita, Morihiro Aoyagi, Takashi Hirao, Yoshihiro Yamanishi

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引用次数: 0

Abstract

Foods possess a range of unexplored functionalities; however, fully identifying these functions through empirical means presents significant challenges. In this study, we have proposed an in silico approach to comprehensively predict the functionalities of foods, encompassing even processed foods. This prediction is accomplished through the utilization of machine learning on biomedical big data. Our focus revolves around disease-related protein pathways, wherein we statistically evaluate how the constituent compounds collaboratively regulate these pathways. The proposed method has been employed across 876 foods and 83 diseases, leading to an extensive revelation of both food functionalities and their underlying operational mechanisms. Additionally, this approach identifies food combinations that potentially affect molecular pathways based on interrelationships between food functions within disease-related pathways. Our proposed method holds potential for advancing preventive healthcare.

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通过机器学习揭示食品的综合功能和作用机理。

食品具有一系列尚未开发的功能；然而，通过经验手段全面确定这些功能是一项重大挑战。在这项研究中，我们提出了一种硅学方法来全面预测食品的功能，甚至包括加工食品。这种预测是通过对生物医学大数据的机器学习来实现的。我们的重点是围绕与疾病相关的蛋白质通路，通过统计评估组成化合物如何协同调节这些通路。我们已在 876 种食物和 83 种疾病中采用了所提出的方法，从而广泛揭示了食物的功能及其潜在的运行机制。此外，这种方法还能根据食物功能在疾病相关途径中的相互关系，确定可能影响分子途径的食物组合。我们提出的方法具有推进预防保健的潜力。

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来源期刊

Journal of Chemical Information and Modeling 化学-化学综合

CiteScore

9.80

自引率

10.70%

发文量

529

审稿时长

1.4 months

期刊介绍： The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.