Modeling cationic adduction of oligonucleotides using electrospray desorption ionization
JM Sutton, MG Bartlett - Rapid Communications in Mass …, 2020 - Wiley Online Library
JM Sutton, MG Bartlett
Rapid Communications in Mass Spectrometry, 2020•Wiley Online LibraryRationale Cationic adduction causes poor sensitivity and increases spectral complexity
during mass spectral analysis of oligonucleotides and alkylamines are used to reduce this
adduction. It is unclear the effect of the physiochemical properties of the alkylamines on the
reduction of the cationic adduction. Methods All samples were directly infused into a Synapt
G2 HDMS quadrupole time‐of‐flight (TOF) hybrid mass spectrometer in negative ion
electrospray ionization mode through the native built‐in fluidics system. The infusion flow …
during mass spectral analysis of oligonucleotides and alkylamines are used to reduce this
adduction. It is unclear the effect of the physiochemical properties of the alkylamines on the
reduction of the cationic adduction. Methods All samples were directly infused into a Synapt
G2 HDMS quadrupole time‐of‐flight (TOF) hybrid mass spectrometer in negative ion
electrospray ionization mode through the native built‐in fluidics system. The infusion flow …
Rationale
Cationic adduction causes poor sensitivity and increases spectral complexity during mass spectral analysis of oligonucleotides and alkylamines are used to reduce this adduction. It is unclear the effect of the physiochemical properties of the alkylamines on the reduction of the cationic adduction.
Methods
All samples were directly infused into a Synapt G2 HDMS quadrupole time‐of‐flight (TOF) hybrid mass spectrometer in negative ion electrospray ionization mode through the native built‐in fluidics system. The infusion flow rate was set to 50 μL/min. The TOFMS tuning parameters were as follows: capillary voltage −2.0 kV, cone voltage 25 V, extraction cone voltage 2 V, source temperature 125°C, desolvation temperature 450°C, cone gas flow rate 0 L/h, and desolvation gas (nitrogen) flow rate 1000 L/h.
Results
A quantitative model was created to predict the optimized alkylamine for MS analysis, while a qualitative model was generated to explain the most important physiochemical properties: proton affinity (13.83%), gas‐phase basicity (11.79%), pKa (11.47%), boiling point (10.73%), MW (10.3%), Henry's Law Constant (9.56%), and partition coefficient (logP) (9.44%). The quantitative model was applied to RNA (microRNA) and a phosphorothioate and predicts the trend of cationic adduction.
Conclusions
Two models are described to understand the physiochemical properties that contribute to the adduction and to provide users a quick mathematical tool to predict the best choice of alkylamine to lower cationic adduction and decrease spectral complexity while enhancing sensitivity.
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