QSAR in natural non-peptidic food-related compounds: Current status and future perspective

Bioactive factors in functional foods play a crucial role in performing their specific functions. These factors have their own specific physical and chemical properties, and more importantly, they have specific interactions with other components in the food system to produce the desired functions. With the rapid development and integration of computer science, chemistry, biology, mathematics, and other related fields, data-driven quantitative structure-activity relationship (QSAR) has emerged as a crucial tool for all fields of food research. However, there is still a lack of a comprehensive review of the QSAR of natural non-peptidic food-related products. We focus on recent advancements in the theories, current applications, and status of QSAR methods in food science and related fields. We summarize an overview of the emerging trends, future directions, and limitations of various methods, as well as explore the implications of QSAR methods in improving food quality, safety, and nutrition in the ever-evolving landscape of food science research. QSAR plays a significant role in predicting, discovering, designing, and screening of non-peptidic food-related natural products, and interpreting the functional mechanisms. In particular, the use of artificial intelligence-based methods is expected to drive new advancements in the application of QSAR methods. [Display omitted] •QSAR has promoted the development of functional foods containing natural products.•Artificial intelligence (AI) improves the prediction accuracy and efficiency of QSAR.•AI-QSAR drives a deeper exploration of the structure-activity relationships.