J Phys Chem Lett. 2024 Aug 19:8697-8705. doi: 10.1021/acs.jpclett.4c01954. Online ahead of print.
ABSTRACT
In this work, we study the synthesis of glycine, the simplest amino acid, using ab initio molecular dynamics and enhanced sampling techniques to explore and quantify novel potential pathways. Our protocol integrates state-of-the-art machine learning approaches, allowing us to sample relevant chemical spaces more efficiently. We discover a novel “oxyglycolate path”, distinct from the “standard” Strecker mechanism, identify new intermediates, and provide a full thermodynamic characterization of all reaction steps. This alternative pathway aligns better with meteoritic and experimental observations, paving the way for further investigations. Integrating quantum accuracy and machine learning in prebiotic chemistry represents a methodological milestone advancing the exploration of life’s prebiotic origins.
PMID:39159425 | DOI:10.1021/acs.jpclett.4c01954
