Competing Reaction Mechanisms of Peptide Bond Formation in Water Revealed by Deep Potential Molecular Dynamics and Path Sampling

化学 分子动力学 肽键 水溶液 计算化学 分子 生物系统 有机化学 生物化学 生物
作者
Rolf David,Iñaki Tuñón,Damien Laage
出处
期刊:Journal of the American Chemical Society [American Chemical Society]
卷期号:146 (20): 14213-14224 被引量:5
标识
DOI:10.1021/jacs.4c03445
摘要

The formation of an amide bond is an essential step in the synthesis of materials and drugs, and in the assembly of amino acids to form peptides. The mechanism of this reaction has been studied extensively, in particular to understand how it can be catalyzed, but a representation capable of explaining all the experimental data is still lacking. Numerical simulation should provide the necessary molecular description, but the solvent involvement poses a number of challenges. Here, we combine the efficiency and accuracy of neural network potential-based reactive molecular dynamics with the extensive and unbiased exploration of reaction pathways provided by transition path sampling. Using microsecond-scale simulations at the density functional theory level, we show that this method reveals the presence of two competing distinct mechanisms for peptide bond formation between alanine esters in aqueous solution. We describe how both reaction pathways, via a general base catalysis mechanism and via direct cleavage of the tetrahedral intermediate respectively, change with pH. This result contrasts with the conventional mechanism involving a single pathway in which only the barrier heights are affected by pH. We show that this new proposal involving two competing mechanisms is consistent with the experimental data, and we discuss the implications for peptide bond formation under prebiotic conditions and in the ribosome. Our work shows that integrating deep potential molecular dynamics with path sampling provides a powerful approach for exploring complex chemical mechanisms.

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
刚刚
结实的小土豆完成签到,获得积分10
1秒前
2秒前
粱从寒发布了新的文献求助10
3秒前
3秒前
牛马人生完成签到,获得积分10
5秒前
6秒前
6秒前
chenrujian发布了新的文献求助10
6秒前
wjl发布了新的文献求助10
6秒前
7秒前
8秒前
8秒前
柚子完成签到,获得积分10
8秒前
8秒前
9秒前
桐桐应助心灵美秋珊采纳,获得10
10秒前
10秒前
岁杪完成签到,获得积分10
10秒前
lailai完成签到 ,获得积分10
10秒前
好吃发布了新的文献求助10
11秒前
顾矜应助空古悠浪采纳,获得10
11秒前
chen发布了新的文献求助10
12秒前
王乐多发布了新的文献求助10
12秒前
12秒前
隐形曼青应助大爆炸采纳,获得10
12秒前
那些年发布了新的文献求助10
12秒前
Makkki发布了新的文献求助10
12秒前
Emma发布了新的文献求助10
12秒前
13秒前
13秒前
情怀应助布丁味小核桃采纳,获得10
14秒前
充电宝应助星期一采纳,获得10
15秒前
芬枫疯完成签到 ,获得积分10
15秒前
子车茗应助娇气的寒香采纳,获得30
15秒前
大大完成签到,获得积分10
15秒前
16秒前
情怀应助大河内采纳,获得10
16秒前
芋头发布了新的文献求助10
17秒前
17秒前
高分求助中
Continuum Thermodynamics and Material Modelling 4000
Production Logging: Theoretical and Interpretive Elements 2700
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
El viaje de una vida: Memorias de María Lecea 800
Luis Lacasa - Sobre esto y aquello 700
Novel synthetic routes for multiple bond formation between Si, Ge, and Sn and the d- and p-block elements 700
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 3515448
求助须知:如何正确求助?哪些是违规求助? 3097719
关于积分的说明 9236719
捐赠科研通 2792737
什么是DOI,文献DOI怎么找? 1532622
邀请新用户注册赠送积分活动 712201
科研通“疑难数据库(出版商)”最低求助积分说明 707160