A New Route\nto the Prebiotic Synthesis of Glycine\nvia <i>Ab Initio</i>-Based Machine Learning Calculations

In this work, we study the synthesis of glycine, the\nsimplest amino\nacid, using <i>ab initio</i> molecular dynamics and enhanced\nsampling techniques to explore and quantify novel potential pathways.\nOur protocol integrates state-of-the-art machine learning approaches,\nallowing us to sample relevant chemical spaces more efficiently. We\ndiscover a novel “oxyglycolate path”, distinct from\nthe “standard” Strecker mechanism, identify new intermediates,\nand provide a full thermodynamic characterization of all reaction\nsteps. This alternative pathway aligns better with meteoritic and\nexperimental observations, paving the way for further investigations.\nIntegrating quantum accuracy and machine learning in prebiotic chemistry\nrepresents a methodological milestone advancing the exploration of\nlife’s prebiotic origins.