Abstract
The emergence of life on the prebiotic Earth must have involved the formation of polypeptides, yet the polymerization of amino acids is thermodynamically unfavorable under biologically relevant aqueous conditions because amino acids are zwitterions in solution and because of the production of a water molecule through a condensation reaction. Many mechanisms for overcoming this thermodynamic unfavorability have been proposed, but the role of gas phase water clusters has not been investigated. We present the thermodynamics of the water-mediated gas phase dimerization reaction of glycine as a model for the atmospheric polymerization of amino acids prior to the emergence of biological machinery. We hypothesize that atmospheric aerosols may have played a major role in the prebiotic formation of peptide bonds by providing the thermodynamic driving force to facilitate increasingly stable linear oligopeptides. In addition, we hypothesize that small aerosols orient amino acids on their surfaces, thus providing the correct molecular orientations to funnel the reaction pathways of peptides through transition states that lead eventually to polypeptide products. Using density functional theory and a thorough configurational sampling technique, we show that the thermodynamic spontaneity of the linear dimerization of glycine in the gas phase can be driven by the addition of individual water molecules.
| Original language | English |
|---|---|
| Pages (from-to) | 4150-4159 |
| Number of pages | 10 |
| Journal | Journal of Physical Chemistry A |
| Volume | 124 |
| Issue number | 20 |
| DOIs | |
| State | Published - May 21 2020 |
| Externally published | Yes |
Funding
This work was supported by grants CHE-1229354, CHE-1662030, CHE-1721511, and CHE-1903871 from the National Science Foundation (GCS), the Arnold and Mabel Beckman Foundation Beckman Scholar Award (AGG), and the Barry M. Goldwater Scholarship (AGG). High-performance computing resources were provided by the MERCURY Consortium ( http://www.mercuryconsortium.org ), and molecular graphics were generated with UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from NIH P41-GM103311. Graphs and schematics were created with Python 2.7, Pyplot in Matplotlib 2.0.2, Gaussview 6.0.16. We thank Greg Springsteen for helpful conversations and Berhane Temelso for scientific and technical support.