Characterization of Reaction Products and Mechanisms between Serotonin and Methylglyoxal in Model Reactions and Mice

化学 血清素 甲基乙二醛 代谢物 5-羟色胺能 胺气处理 立体化学 生物化学 有机化学 受体
作者
Yao Tang,Changling Hu,Shengmin Sang
出处
期刊:Journal of Agricultural and Food Chemistry [American Chemical Society]
卷期号:68 (8): 2437-2444 被引量:9
标识
DOI:10.1021/acs.jafc.0c00071
摘要

Serotonin is an important endogenous regulatory neurotransmitter and has also been found in fruits, vegetables, and nuts. Methylglyoxal (MGO) is a reactive dicarbonyl metabolite and also a food toxin that modifies protein and DNA to cause the development of many chronic diseases. The objective of this study is to understand the reaction mechanisms between serotonin and MGO and determine whether serotonin could trap MGO in vivo. Five products were detected in phosphate buffer (pH 7.4) at 37 °C. Four products (compounds 2 and 4–6) were purified from the reaction mixture, and their structures were characterized by the analysis of their high-resolution mass and one- and two-dimensional nuclear magnetic resonance spectra. One product (compound 3), as a result of its instability, could not be properly purified and was tentatively characterized on the basis of its high-resolution mass spectrum and corresponding mass fragments. On the basis of the structures of these five products, two reaction pathways were proposed. Compounds 2, 3, 5, and 6 were produced through the Pictet–Spengler condensation pathway between the primary amine of serotonin and the ketone of MGO, and compound 3 was identified as the intermediate product to form products 2, 5, and 6, whereas compound 4 was formed through nucleophilic substitution by the benzene ring of serotonin, which is a new reaction pathway between biogenic amines and reactive carbonyl species. More importantly, the detection of adducts 2 and 4–6 in mice supports our hypothesis that the reaction between serotonin and MGO also happens in vivo through the same pathways as those in model reactions, suggesting that dietary or endogenous serotonin has the capacity to trap MGO in vivo.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
成就紫真完成签到,获得积分10
刚刚
崔win发布了新的文献求助10
刚刚
RC_Wang应助猛男采纳,获得10
刚刚
刚刚
咚咚完成签到,获得积分10
刚刚
1秒前
1秒前
Owen应助JefreeCN采纳,获得10
1秒前
猪嗝铁铁发布了新的文献求助30
1秒前
oneonedog发布了新的文献求助10
1秒前
2秒前
忐忑的骁发布了新的文献求助10
2秒前
wjx发布了新的文献求助10
2秒前
一念初见完成签到,获得积分10
2秒前
小黑哥发布了新的文献求助10
2秒前
一锅炖不下完成签到 ,获得积分10
3秒前
3秒前
英俊的铭应助泯珉采纳,获得10
4秒前
4秒前
852应助aixue采纳,获得10
4秒前
脑洞疼应助盖斯的可言采纳,获得10
4秒前
xhsz1111发布了新的文献求助10
5秒前
笨笨松发布了新的文献求助10
5秒前
wanci应助田田采纳,获得30
5秒前
淡定成风发布了新的文献求助10
6秒前
苏卿应助成就紫真采纳,获得10
7秒前
夏尔完成签到,获得积分10
7秒前
倦梦还完成签到,获得积分10
7秒前
Xiaohu完成签到,获得积分10
8秒前
9秒前
9秒前
jianxin发布了新的文献求助10
9秒前
热心路人应助等待的觅珍采纳,获得200
9秒前
小黑哥完成签到,获得积分20
10秒前
科研通AI5应助冷酷沛柔采纳,获得10
10秒前
忐忑的骁完成签到,获得积分20
10秒前
10秒前
xxr关注了科研通微信公众号
10秒前
12秒前
12秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 1000
Conference Record, IAS Annual Meeting 1977 710
電気学会論文誌D(産業応用部門誌), 141 巻, 11 号 510
Virulence Mechanisms of Plant-Pathogenic Bacteria 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3564065
求助须知:如何正确求助?哪些是违规求助? 3137276
关于积分的说明 9421653
捐赠科研通 2837658
什么是DOI,文献DOI怎么找? 1559942
邀请新用户注册赠送积分活动 729224
科研通“疑难数据库(出版商)”最低求助积分说明 717215