Fully Automated Generation of Prebiotically Relevant Reaction Networks from Optimized Nanoreactor Simulations

Stan, Alexandra; Esch, Beatriz von der und Ochsenfeld, Christian (2022): Fully Automated Generation of Prebiotically Relevant Reaction Networks from Optimized Nanoreactor Simulations. In: Journal of Chemical Theory and Computation, Bd. 18, Nr. 11: S. 6700-6712

Abstract

The nanoreactor approach first introduced by the gr o u p of Martinez [Wang et al . Nat. Chem. 2014, 6, 1044-1048] has recently attracted much attention because of its abi l i t y to accelerate the discovery of reaction pathways. Here, we provide a comprehensive study of various simulation parameters and present an alternative implementation for the reactivity-enhancing spherical constraint function, as well as for the detection of reaction events. In this context, a fully automated postsimulation evaluation procedure based on RDKit and NetworkX analysis is introduced . The chemical and physical robustness of the procedure is examined by investigating the reacti v i t y of selected homogeneous systems. The optimized procedure is applied at the GFN2-xTB level of theory to a system composed of HCN molecules and argon atoms, acting as a buffer, yielding prebiotically plausible primary and secondary precursors for the synthesis of RNA . Furthermore, the formose reaction network is explored leading to numerous sugar precursors. The discovered compounds reflect experimental findings;howe v e r , new synthetic routes and a large collection of exotic, highly reactive molecules are observed, highlighting the predictive po w e r of the nanoreactor approach for unraveling the reactive manifold.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Chemie und Pharmazie > Department Chemie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 540 Chemie
• ISSN: 1549-9618
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 364653263
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 325871075