David Rolf, Tuñón Iñaki, Laage Damien
PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France.
Departamento de Química Física, Universitat de Valencia, Burjassot, 46100 Valencia, Spain.
J Am Chem Soc. 2024 May 22;146(20):14213-14224. doi: 10.1021/jacs.4c03445. Epub 2024 May 13.
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.
酰胺键的形成是材料与药物合成以及氨基酸组装形成肽过程中的关键步骤。该反应的机制已得到广泛研究,特别是为了理解其催化方式,但仍缺乏一种能够解释所有实验数据的表述。数值模拟应能提供必要的分子描述,但溶剂的参与带来了诸多挑战。在此,我们将基于神经网络势的反应性分子动力学的效率与准确性,与过渡路径采样所提供的对反应路径的广泛且无偏探索相结合。通过在密度泛函理论水平上进行微秒级模拟,我们表明该方法揭示了水溶液中丙氨酸酯之间肽键形成存在两种相互竞争的不同机制。我们描述了这两种反应途径,分别通过一般碱催化机制和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对比,在传统机制中只有势垒高度受pH值影响。我们表明,这个涉及两种竞争机制的新观点与实验数据一致,并且我们讨论了其对益生元条件下以及核糖体中肽键形成的影响。我们的工作表明,将深度势分子动力学与路径采样相结合为探索复杂化学机制提供了一种强大的方法。