Literature DB >> 22956322

Correlation of Ecom50 values between mass spectrometers: effect of collision cell radiofrequency voltage on calculated survival yield.

Dennis W Hill1, Clive L Baveghems, Daniel R Albaugh, Tzipporah M Kormos, Steven Lai, Hank K Ng, David F Grant.   

Abstract

RATIONALE: The determination of the center-of-mass energy at which 50% of a precursor ion decomposes (Ecom(50)) during collision-induced dissociation (CID) is dependent on the chemical structure of the ion as well as the physical and electrical characteristics of the collision cell. The current study was designed to identify variables influencing Ecom(50) values measured on four different mass spectrometers.
METHODS: Fifteen test compounds were protonated using + ve electrospray ionization and the resulting ions were fragmented across a range of collision energies by CID. Survival yield versus collision energy curves were then used to calculate Ecom(50) values for each of these [M+H](+) ions on four different mass spectrometers. In addition, the relative recovery of the [M+H](+) ions of eight compounds ranging in molecular weight from 46 to 854 Da were determined at collision cell radiofrequency (RF) voltages ranging from 0 to 600 V.
RESULTS: Ecom(50) values determined on the four instruments were highly correlated (r(2) values ranged from 0.953 to 0.992). Although these overall correlations were high, we found different maximum ion recoveries depending on collision cell RF voltage. High-mass ions had greater recovery at higher collision cell RF voltages, whereas low-mass ions had greater recovery at lower collision cell RF voltages as well as a broader range of ion recoveries.
CONCLUSIONS: Ecom(50) values measured on four different instruments correlated surprisingly well given the differences in electrical and physical characteristics of the collision cells. However, our results suggest caution when comparing Ecom(50) values or CID spectra between instruments without correcting for the effects of RF voltage on ion transfer efficiency.
Copyright © 2012 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22956322      PMCID: PMC3439163          DOI: 10.1002/rcm.6353

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  11 in total

Review 1.  MassKinetics: a theoretical model of mass spectra incorporating physical processes, reaction kinetics and mathematical descriptions.

Authors:  L Drahos; K Vékey
Journal:  J Mass Spectrom       Date:  2001-03       Impact factor: 1.982

Review 2.  Internal energy and fragmentation of ions produced in electrospray sources.

Authors:  Valérie Gabelica; Edwin De Pauw
Journal:  Mass Spectrom Rev       Date:  2005 Jul-Aug       Impact factor: 10.946

3.  Monte Carlo/RRKM/classical trajectories modeling of collisional excitation and dissociation of n-butylbenzene ion in multipole collision cells of tandem mass spectrometers.

Authors:  Vadim D Knyazev; Stephen E Stein
Journal:  J Phys Chem A       Date:  2010-06-10       Impact factor: 2.781

Review 4.  Ion activation methods for tandem mass spectrometry.

Authors:  Lekha Sleno; Dietrich A Volmer
Journal:  J Mass Spectrom       Date:  2004-10       Impact factor: 1.982

5.  Absolute Rate Theory for Isolated Systems and the Mass Spectra of Polyatomic Molecules.

Authors:  H M Rosenstock; M B Wallenstein; A L Wahrhaftig; H Eyring
Journal:  Proc Natl Acad Sci U S A       Date:  1952-08       Impact factor: 11.205

6.  Fragmentation of benzylpyridinium "thermometer" ions and its effect on the accuracy of internal energy calibration.

Authors:  Konstantin V Barylyuk; Konstantin Chingin; Roman M Balabin; Renato Zenobi
Journal:  J Am Soc Mass Spectrom       Date:  2009-10-06       Impact factor: 3.109

7.  CE50: quantifying collision induced dissociation energy for small molecule characterization and identification.

Authors:  Tzipporah M Kertesz; Lowell H Hall; Dennis W Hill; David F Grant
Journal:  J Am Soc Mass Spectrom       Date:  2009-06-21       Impact factor: 3.109

8.  Mass spectrometric characterization of 3'-imino[60]fulleryl-3'-deoxythymidine by collision-induced dissociation.

Authors:  Jean-François Greisch; Edwin De Pauw
Journal:  J Mass Spectrom       Date:  2007-03       Impact factor: 1.982

9.  Development of Ecom₅₀ and retention index models for nontargeted metabolomics: identification of 1,3-dicyclohexylurea in human serum by HPLC/mass spectrometry.

Authors:  L Mark Hall; Lowell H Hall; Tzipporah M Kertesz; Dennis W Hill; Thomas R Sharp; Edward Z Oblak; Ying W Dong; David S Wishart; Ming-Hui Chen; David F Grant
Journal:  J Chem Inf Model       Date:  2012-04-27       Impact factor: 4.956

10.  Comparison of the internal energy deposition of Venturi-assisted electrospray ionization and a Venturi-assisted array of micromachined ultrasonic electrosprays (AMUSE).

Authors:  Christina Y Hampton; Catherine J Silvestri; Thomas P Forbes; Mark J Varady; J Mark Meacham; Andrei G Fedorov; F Levent Degertekin; Facundo M Fernández
Journal:  J Am Soc Mass Spectrom       Date:  2008-06-28       Impact factor: 3.109

View more
  6 in total

1.  In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics.

Authors:  Lochana C Menikarachchi; Dennis W Hill; Mai A Hamdalla; Ion I Mandoiu; David F Grant
Journal:  J Chem Inf Model       Date:  2013-09-12       Impact factor: 4.956

2.  Optimizing artificial neural network models for metabolomics and systems biology: an example using HPLC retention index data.

Authors:  L Mark Hall; Dennis W Hill; Lochana C Menikarachchi; Ming-Hui Chen; Lowell H Hall; David F Grant
Journal:  Bioanalysis       Date:  2015       Impact factor: 2.681

3.  Correction of precursor and product ion relative abundances in order to standardize CID spectra and improve Ecom50 accuracy for non-targeted metabolomics.

Authors:  Ritvik Dubey; Dennis W Hill; Steven Lai; Chen Ming-Hui; David F Grant
Journal:  Metabolomics       Date:  2015-06-01       Impact factor: 4.290

4.  MolFind: a software package enabling HPLC/MS-based identification of unknown chemical structures.

Authors:  Lochana C Menikarachchi; Shannon Cawley; Dennis W Hill; L Mark Hall; Lowell Hall; Steven Lai; Janine Wilder; David F Grant
Journal:  Anal Chem       Date:  2012-10-23       Impact factor: 6.986

Review 5.  Chemical structure identification in metabolomics: computational modeling of experimental features.

Authors:  Lochana C Menikarachchi; Mai A Hamdalla; Dennis W Hill; David F Grant
Journal:  Comput Struct Biotechnol J       Date:  2013-03-01       Impact factor: 7.271

6.  Development of Database Assisted Structure Identification (DASI) Methods for Nontargeted Metabolomics.

Authors:  Lochana C Menikarachchi; Ritvik Dubey; Dennis W Hill; Daniel N Brush; David F Grant
Journal:  Metabolites       Date:  2016-05-31
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.