Identification and Characterization of Novel Umami and Umami-Enhancing Peptides from Soy Sauce Using an In Silico Approach and Electronic Tongue

The objective of the study was to discover novel umami and umami-enhancing peptides in soy sauce and to elucidate the molecular mechanism underlying their umami-enhancing effect. Soy sauce peptides were isolated by resin adsorption and ethanol elution, identified by UPLC-MS/MS, and screened with multiple virtual tools. Results showed that 159 peptides were identified, and four of them, GAAGAAD, HQADGKS, GDDDEVEAAM, and MPPTEPECEK, were predicted to have a potential umami taste. Subsequently, the electronic tongue results suggested GAAGAAD having the strongest umami taste, followed by MPPTEPECEK, GDDDEVEAAM, and HQADGKS. Moreover, GAAGAAD, HQADGKS, and MPPTEPECEK all enhanced umami in sodium glutamate solution, with GAAGAAD showing the most potent effect, increasing umami intensity by 22.3%. Molecular docking revealed that GAAGAAD exhibited a lower binding energy when docked to the T1R1/T1R3-Glu complex compared to T1R1/T1R3 alone, mainly due to the production of more hydrogen bond interactions to enhance its stability, which may be the reason for its umami-enhancing effect. Furthermore, the peptide enhanced the stability of the receptor-Glu complex, potentially explaining its ability to enhance the umami of Glu. This work provides mechanistic insight into the enhancement of umami by soy sauce peptides, highlighting their potential as ingredients for seasoning formulations.

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Publication Details

Journal
Foods
Published
2026-02-12
DOI
https://doi.org/10.3390/foods15040680
Primary Topic
Biochemical Analysis and Sensing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Identification and Characterization of Novel Umami and Umami-Enhancing Peptides from Soy Sauce Using an In Silico Approach and Electronic Tongue

S. Chen, Long Ding, Tianliang Wu, Ting Cai et al.
Foods
Biochemical Analysis and Sensing Techniques
article

Identification and Characterization of Novel Umami and Umami-Enhancing Peptides from Soy Sauce Using an In Silico Approach and Electronic Tongue

S. Chen, Long Ding, Tianliang Wu, Ting Cai, Ying Su, Zhiqing Lin, Huan Liu
article en

Abstract

The objective of the study was to discover novel umami and umami-enhancing peptides in soy sauce and to elucidate the molecular mechanism underlying their umami-enhancing effect. Soy sauce peptides were isolated by resin adsorption and ethanol elution, identified by UPLC-MS/MS, and screened with multiple virtual tools. Results showed that 159 peptides were identified, and four of them, GAAGAAD, HQADGKS, GDDDEVEAAM, and MPPTEPECEK, were predicted to have a potential umami taste. Subsequently, the electronic tongue results suggested GAAGAAD having the strongest umami taste, followed by MPPTEPECEK, GDDDEVEAAM, and HQADGKS. Moreover, GAAGAAD, HQADGKS, and MPPTEPECEK all enhanced umami in sodium glutamate solution, with GAAGAAD showing the most potent effect, increasing umami intensity by 22.3%. Molecular docking revealed that GAAGAAD exhibited a lower binding energy when docked to the T1R1/T1R3-Glu complex compared to T1R1/T1R3 alone, mainly due to the production of more hydrogen bond interactions to enhance its stability, which may be the reason for its umami-enhancing effect. Furthermore, the peptide enhanced the stability of the receptor-Glu complex, potentially explaining its ability to enhance the umami of Glu. This work provides mechanistic insight into the enhancement of umami by soy sauce peptides, highlighting their potential as ingredients for seasoning formulations.

FoodsVol. 15(4)
ZheJiang Institute For Food and Drug Control (CN), Chongqing University of Technology (CN), Northwest A&F University (CN)
Natural Science Foundation of Chongqing, Centre Scientifique et Technique du Bâtiment
Openalex Percentile: Top 57%
Biochemical Analysis and Sensing Techniques
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Identification and Characterization of Novel Umami and Umami-Enhancing Peptides from Soy Sauce Using an In Silico Approach and Electronic Tongue — S. Chen, Long Ding, et al. · Foods (2026) | TGRS Research Map | TGRS