Oligonucleotides: degradation studies
70th ASMS Conference on Mass Spectrometry. June 2022
Ismael Zamora1; Fabien Fontaine1; Tatiana Radchenko1; Bridget Becker2; Robert Greene2
1Lead Molecular Design, S.L., Sant Cugat del Valles, Spain; 2LabCorp Madison WI USA, Madison, WI
Abstract
Introduction
The study of the biotransformation products for therapeutic oligonucleotides using LC-MS is challenging issue due to the high molecular weight of this class of compounds. Since these compounds are composed of multiple monomers that can undergo metabolic reactions such as phosphodiester hydrolysis, this makes building the virtual set of all potential metabolites time and computational resource intensive. In addition, due to the high number of cleavable bonds, the fragmentation analysis requires even more time and computing power. Finally, there is a third challenge related to the depiction of the parent and the metabolites as atoms/bonds in a manner suitable for an algorithm to predict where in the molecule the metabolic reaction occurs.
Methods
New algorithms that address the challenges in highly modified therapeutic oligonucleotide structure elucidation have been developed. The peak detection algorithm was improved to use the Most Abundant Isotope for parent and potential metabolites. A new algorithm is producing all virtual metabolites applying the library of chemical reactions to each monomer while maintain the connection to the atoms. A third improvement it is the fragmentation algorithm that has two layers of analysis at monomer levels and the other at the bond levels. Finally, we will also show the results of the implemented algorithm for the analysis results visualization.
Preliminary data
The developed algorithm has been applied to a collection of experimental data for a set of oligonucleotides where the data was collected on a Q-Exactive instrument in negative ionization mode. The oligonucleotides have a molecular weight in the range of 7500 Daltons and contain 20 monomers that were a mixed of natural and non-natural nucleotides. Each construct was incubated in the presence of human or monkey liver homogenate for up to 72 hours to generate the metabolites for this project.
More than 10 biotransformation products were detected for each analyte with high mass accuracy (< 5 ppm). The majority of the metabolites resulted from one metabolic modification, but also compounds resulting from two biotransformations were detected by the new algorithm. Each of these compounds showed a suitable fragmentation pattern that could be compared to the parent by the fragmentation algorithm to assign the shifted and non-shifted fragments. For example, the most abundant metabolite accounted for 11.1 % of the total chromatogram area in one of the incubations, had an 0.16 ppm mass accuracy and had more than 120 fragments that could be used to identify its structure with a MassMetaSite score higher than 3322. The assigned structure corresponds to cleavage of the terminal nucleotide from the parent. The second most abundant metabolite had a mass accuracy of 0.60 ppm, a charge of minus 9, and over 100 assigned fragments yielding a MassMetaSite score of almost 5000.
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