Developing unsupervised computation techniques for the structural elucidation of molecules from complex mixtures.

Carlos A. Acosta Jr.¹ , Paolo Benigni¹ , Francisco Fernandez-Lima^1,2

1 Department of Chemistry and Biochemistry, Florida International University, Miami, USA
2 Biomolecular Science Institute, Florida International University, Miami, USA

Knowing the chemical structure of a molecule is fundamental to understanding its properties and predicting its chemical behavior. However, determining the structure of a molecule in a complex mixtures is very challenging, particularly in mixtures such as crude oil and dissolved organic matter. In this study, we are developing a method for determining the chemical structure of molecules in a complex mixture utilizing TIMS-FT-ICR MS and computational tools. This work expands the Software Assisted Molecular Elucidation (SAME) package by expanding the theoretical tools with accurate mass and mobility experimental datasets. A significant challenge in SAME is that the number of potential structures for a given chemical formula increases exponentially as the number of carbon atoms in the formula increases; if unguided, the number of potential structures can quickly, escalate and becomes computationally challenging. In this work, a SAME package can use raw data obtained from analytical instruments, collect the information which is relevant to the sorting process and store it in a database. This database can then be used to quickly compare the theoretical calculations for the parameters in question and match them with the experimentally derived values.