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

The nanoreactor approach first introduced by the group
of Martı́nez
[Wang et al. Nat. Chem. 2014, 6, 1044–1048] has recently attracted much attention
because of its ability 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 reactivity 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;
however, new synthetic routes and a large collection of exotic, highly
reactive molecules are observed, highlighting the predictive power
of the nanoreactor approach for unraveling the reactive manifold.