Application of quantitative structure-activity relationship to food-derived peptides: Methods, situations, challenges and prospects. (August 2021)
- Record Type:
- Journal Article
- Title:
- Application of quantitative structure-activity relationship to food-derived peptides: Methods, situations, challenges and prospects. (August 2021)
- Main Title:
- Application of quantitative structure-activity relationship to food-derived peptides: Methods, situations, challenges and prospects
- Authors:
- Bo, Weichen
Chen, Lang
Qin, Dongya
Geng, Sheng
Li, Jiaqi
Mei, Hu
Li, Bo
Liang, Guizhao - Abstract:
- Abstract: Background: Food-derived bioactive peptides have attracted extensive attention because of their antioxidant, antibacterial, antitumor and antihypertensive effects. The conventional approaches used to acquire bioactive peptides require complicated procedures involving enzymolysis, separation and identification. So far, data-driven computing methods have become an important tool for the screening, design and mechanism exploration of bioactive peptides. The quantitative structure-activity relationship (QSAR), a quantitative method used to describe the structure-activity relationship of compounds, has been widely used in drug design, material science, and chemistry; however, there are limited applications in food science. Scope and approach: Here, we mainly focus on technologies used to perform QSAR modeling in peptides, including dataset collection, structural characterization, variable selection, correlation methods, and model validation and evaluation. We also summarize the recent applications, situations, challenges and prospects of the use of QSAR in food-derived bioactive peptides. Key findings and conclusions: Researchers should make full use of the benefits of QSAR as well as face its challenges. Multiple new methods or combination strategies should be used to achieve QSAR analysis. Much research is needed to improve the knowledge of QSAR in order to discover bioactive peptides. The solution to this task requires multidisciplinary cooperation in multipleAbstract: Background: Food-derived bioactive peptides have attracted extensive attention because of their antioxidant, antibacterial, antitumor and antihypertensive effects. The conventional approaches used to acquire bioactive peptides require complicated procedures involving enzymolysis, separation and identification. So far, data-driven computing methods have become an important tool for the screening, design and mechanism exploration of bioactive peptides. The quantitative structure-activity relationship (QSAR), a quantitative method used to describe the structure-activity relationship of compounds, has been widely used in drug design, material science, and chemistry; however, there are limited applications in food science. Scope and approach: Here, we mainly focus on technologies used to perform QSAR modeling in peptides, including dataset collection, structural characterization, variable selection, correlation methods, and model validation and evaluation. We also summarize the recent applications, situations, challenges and prospects of the use of QSAR in food-derived bioactive peptides. Key findings and conclusions: Researchers should make full use of the benefits of QSAR as well as face its challenges. Multiple new methods or combination strategies should be used to achieve QSAR analysis. Much research is needed to improve the knowledge of QSAR in order to discover bioactive peptides. The solution to this task requires multidisciplinary cooperation in multiple fields, including chemistry, computer science, mathematics and, of course, food science. Highlights: This review emphasizes the application of QSAR to food-derived peptides. Multiple methods or combination strategies should be used to achieve QSAR analysis. Researchers should reveal the benefits of QSAR as well as face its challenges. Much research is needed to improve the knowledge of QSAR to discover peptides. … (more)
- Is Part Of:
- Trends in food science & technology. Volume 114(2021)
- Journal:
- Trends in food science & technology
- Issue:
- Volume 114(2021)
- Issue Display:
- Volume 114, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 114
- Issue:
- 2021
- Issue Sort Value:
- 2021-0114-2021-0000
- Page Start:
- 176
- Page End:
- 188
- Publication Date:
- 2021-08
- Subjects:
- Quantitative structure-activity relationship (QSAR) -- Bioinformatics -- Peptide -- Functional food -- Modeling
Food industry and trade -- Periodicals
Food -- Biotechnology -- Periodicals
664.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09242244 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tifs.2021.05.031 ↗
- Languages:
- English
- ISSNs:
- 0924-2244
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9049.593000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 17433.xml