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Article Dans Une Revue Analytical Chemistry Année : 2022

Network Analysis Reveals Spatial Clustering and Annotation of Complex Chemical Spaces: Application to Astrochemistry

Résumé

How are molecules linked to each other in complex systems? In a proof-of-concept study, we have developed the method mol2net (https://zenodo.org/record/7025094) to generate and analyze the molecular network of complex astrochemical data (from high-resolution Orbitrap MS 1 analysis of H 2 O:CH 3 OH:NH 3 interstellar ice analogs) in a data-driven and unsupervised manner, without any prior knowledge about chemical reactions. The molecular network is clustered according to the initial NH 3 content and unlocked HCN, NH 3 , and H 2 O as spatially resolved key transformations. In comparison with the PubChem database, four subsets were annotated: (i) saturated C-backbone molecules without N, (ii) saturated N-backbone molecules, (iii) unsaturated C-backbone molecules without N, and (iv) unsaturated N-backbone molecules. These findings were validated with previous results (e.g., identifying the two major graph components as previously described N-poor and N-rich molecular groups) but with additional information about subclustering, key transformations, and molecular structures, and thus, the structural characterization of large complex organic molecules in interstellar ice analogs has been significantly refined.
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hal-03854790 , version 1 (16-11-2022)

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Paternité - Pas d'utilisation commerciale - Pas de modification

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Alexander Ruf, Grégoire Danger. Network Analysis Reveals Spatial Clustering and Annotation of Complex Chemical Spaces: Application to Astrochemistry. Analytical Chemistry, 2022, 94 (41), pp.14135-14142. ⟨10.1021/acs.analchem.2c01271⟩. ⟨hal-03854790⟩

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