An in silico model to predict and estimate digestion-resistant and bioactive peptide content of dairy products: A primarily study of a time-saving and affordable method for practical research purposes

被引：25

作者：

Barati, Meisam ^{[1
]}

Javanmardi, Fardin ^{[2
]}

Jabbari, Masoumeh ^{[3
]}

Mokari-Yamchi, Amin ^{[3
]}

Farahmand, Fariba ^{[4
]}

Es, Ismail ^{[5
]}

Farhadnejad, Hossein ^{[6
]}

Davoodi, Sayed Hossein ^{[7
]}

Khaneghah, Amin Mousavi ^{[8
]}

机构：

[1] Shahid Beheshti Univ Med Sci, Fac Nutr & Food Technol, Dept Cellular & Mol Nutr, Student Res Comm, Tehran, Iran

[2] Shahid Beheshti Univ Med Sci, Fac Nutr & Food Technol, Dept Food Sci & Technol, Tehran, Iran

[3] Shahid Beheshti Univ Med Sci, Fac Nutr & Food Technol, Dept Community Nutr, Tehran, Iran

[4] Univ Tehran Med Sci, Sch Nutr Sci & Dietet, Dept Community Nutr, Tehran, Iran

[5] Univ Estadual Campinas, Sch Chem Engn, Dept Mat & Bioproc Engn, UNICAMP, Campinas, SP, Brazil

[6] Shahid Beheshti Univ Med Sci, Nutr & Endocrine Res Ctr, Res Inst Endocrine Sci, Tehran, Iran

[7] Shahid Beheshti Univ Med Sci, Canc Res Ctr, Tehran, Iran

[8] Univ Estadual Campinas, Fac Food Engn, Dept Food Sci, UNICAMP, Sao Paulo, Brazil

来源：

LWT-FOOD SCIENCE AND TECHNOLOGY | 2020年 / 130卷

关键词：

Food proteins; Bioactive peptides; In silico; Functional food; Dairy products; BIOPEP DATABASE; INFANT FORMULA; VIVO; CASEIN; FOOD; RELEASE; MILK; NUTRACEUTICALS; CHALLENGES; PROBIOTICS;

D O I：

10.1016/j.lwt.2020.109616

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

The purpose of this study is to estimate the concentration of digestion-resistant and bioactive peptides in dairy products using an in silico method. The major contributors of milk protein sequences including alpha(s1)-casein, alpha(s)(2)-casein, beta-casein, k-casein, beta-lactoglobulin, and alpha-lactalbumin were obtained from UniProt Knowledge-base (UniProtKB). In silico digestion and bioactive fragment, findings were analyzed using the BIOPEP tool. Bioactive peptide content of the dairy products was estimated based on molecular weight, percent of major proteins existing in the food items, and the number of peptides obtained after in silico digestion from each protein. The results showed that 100 g milk contains 6700.241 mu mol digestion-resistant peptides; in which 1880.434 mu mol out of total peptides have anti-diabetic properties. Of all digestion-resistant peptides, 1978.24, 1955.024, 1700.907, and 1066.07 mu mol belong to very low, low, medium, and high bioactivity sub-groups, respectively. Using the data introduced here, risk assessment could be done for dairy originated bioactive peptides and chronic disease.

引用

页数：12

共 45 条

[31] Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity [J].