Kinetics of prebiotic depsipeptide formation from the ester–amide exchange reaction

Literature Information

Publication Date 2016-09-21
DOI 10.1039/C6CP05527C
Impact Factor 3.676
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Abstract

In this work, we introduce a kinetic model to study the effectiveness of ester-mediated amide bond formation under prebiotic conditions. In our previous work, we found that a simple system composed of α-hydroxy acids and α-amino acids is capable of forming peptide bonds via esterification followed by the ester–amide exchange reaction. To further understand the kinetic behavior of this copolymerization, we first tracked the growth of initial species from a valine/lactic acid mixture in a closed system reactor. A mathematical model was developed to simulate the reactions and evaluate the rate constants at different temperatures. We found these reactions can be described by the empirical Arrhenius equation even when reaction occurred in the solid (dry) state. Further calculations for activation parameters showed that the ester-mediated pathway facilitates amide bond formation by lowering activation entropies. These results provide a theoretical framework that illustrates why the ester-mediated pathway for peptide bond formation is efficient and why it would have been more favorable on the early Earth, compared to peptide bond formation without the aid of hydroxy acids.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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