Detecting low-level synthesis impurities in modified phosphorothioate oligonucleotides using liquid chromatography–high resolution mass spectrometry

Abstract

Oligonucleotide phosphorothioatediesters (phosphorothioate oligonucleotides), in which one of the non-bridging oxygen atoms at each phosphorus center is replaced by a sulfur atom, are now one of the most popular oligonucleotide modifications due to their ease of chemical synthesis and advantageous pharmacokinetic properties. Despite significant progress in the solid-phase oligomerization chemistry used in the manufacturing of these oligonucleotides, multiple classes of low-level impurities always accompany synthetic oligonucleotides. Liquid chromatography–mass spectrometry has emerged as a powerful technique for the identification of these synthesis impurities. However, impurity profiling, where the entire complement of low-level synthetic impurities is identified in a single analysis, is more challenging. Here we present an LC–MS method based the use of high resolution-mass spectrometry, specifically Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS or FTMS). The optimal LC–FTMS conditions, including the stationary phase and mobile phases for the separation and identification of phosphorothioate oligonucleotides, were found. The characteristics of FTMS enable charge state determination from single m/z values of low-level impurities. Charge state information then enables more accurate modeling of the detected isotopic distribution for identification of the chemical composition of the detected impurity. Using this approach, a number of phosphorothioate impurities can be detected by LC–FTMS including failure sequences carrying 3′-terminal phosphate monoester and 3′-terminal phosphorothioate monoester, incomplete backbone sulfurization and desulfurization products, high molecular weight impurities, and chloral, isobutyryl, and N3 (2-cyanoethyl) adducts of the full-length product. When compared with low resolution LC–MS, ∼60% more impurities can be identified when charge state and isotopic distribution information is available and used for impurity profiling.