首页|New Findings Reported from Guangdong Ocean University Describe Advances in Machi ne Learning (Screening and Characterization of Umami Peptides From Enzymatic and Fermented Products of Wheat Gluten Using Machine Learning)

New Findings Reported from Guangdong Ocean University Describe Advances in Machi ne Learning (Screening and Characterization of Umami Peptides From Enzymatic and Fermented Products of Wheat Gluten Using Machine Learning)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning. According to news reporting from Yangjiang, People's Republic of Chin a, by NewsRx journalists, research stated, "To explore the umami peptides from w heat gluten hydrolysates (WGHs) with different degrees of hydrolysis (DH) after Corynebacterium glutamicum (C. glutamicum) fermentation, a high-throughput scree ning method for umami peptides was established based on machine learning. The re sults showed fermented WGHs with high DHs exhibited more favourable taste profil e after 4 days of fermentation and produced more small molecule peptides." The news correspondents obtained a quote from the research from Guangdong Ocean University, "Fermentation increased the number of characteristic peptides in WGH s with DH10, DH15, and DH20. Among, fermented WGHs with DH15 were the important source of potential umami peptides. Six potential umami peptides were screened ( QQLPQFEE, LSFE, EELR, YTCE, YTTD, EEDQ) and were demonstrated to form stable com plex with the T1R1/T1R3 receptor through hydrogen bonding interactions, electros tatic interactions, and hydrophobic interactions forces. The affinity of peptide s and receptor were in the range of -6.3 to -8.1 kcal/ mol. GLU735, GLY755, SER7 34, SER757 and THR227 were the critical binding sites. Sensory evaluation and el ectronic tongue showed that six peptides exhibited umami profile and had the cap acity to enhance umami and saltiness taste. EEDQ presented the strongest intensi ty of umami taste and QQLPQFEE had the lowest umami thresholds."

YangjiangPeople's Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningPeptidesPeptides and Pr oteinsProteinsProteomicsGuangdong Ocean University

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.4)