{"title":"Computational approaches to predict the toxicity of bioactive natural products: a mini review of methodologies","authors":"Kwanyong Choi, Ji Yeon Kim","doi":"10.1007/s10068-024-01701-1","DOIUrl":null,"url":null,"abstract":"<p>Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.</p>","PeriodicalId":566,"journal":{"name":"Food Science and Biotechnology","volume":"41 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Science and Biotechnology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1007/s10068-024-01701-1","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.
期刊介绍：
The FSB journal covers food chemistry and analysis for compositional and physiological activity changes, food hygiene and toxicology, food microbiology and biotechnology, and food engineering involved in during and after food processing through physical, chemical, and biological ways. Consumer perception and sensory evaluation on processed foods are accepted only when they are relevant to the laboratory research work. As a general rule, manuscripts dealing with analysis and efficacy of extracts from natural resources prior to the processing or without any related food processing may not be considered within the scope of the journal. The FSB journal does not deal with only local interest and a lack of significant scientific merit. The main scope of our journal is seeking for human health and wellness through constructive works and new findings in food science and biotechnology field.
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