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.

中文翻译：

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深势分子动力学和路径采样揭示水中肽键形成的竞争反应机制


酰胺键的形成是材料和药物合成以及氨基酸组装形成肽的重要步骤。该反应的机理已被广泛研究，特别是了解它是如何催化的，但仍然缺乏能够解释所有实验数据的表示。数值模拟应该提供必要的分子描述，但溶剂的参与带来了许多挑战。在这里，我们将基于神经网络势的反应分子动力学的效率和准确性与过渡路径采样提供的对反应路径的广泛和公正的探索结合起来。使用密度泛函理论水平的微秒级模拟，我们表明该方法揭示了水溶液中丙氨酸酯之间肽键形成的两种竞争的不同机制的存在。我们描述了两种反应途径（分别通过一般碱催化机制和通过四面体中间体的直接裂解）如何随 pH 值变化。这一结果与涉及单一途径的传统机制形成鲜明对比，在传统机制中，仅势垒高度受 pH 影响。我们表明，这一涉及两种竞争机制的新提议与实验数据一致，并且我们讨论了在生命前条件下和核糖体中肽键形成的影响。我们的工作表明，将深势分子动力学与路径采样相结合，为探索复杂的化学机制提供了一种强大的方法。