Using ‘small molecule’ CCS from
Ion Mobility Mass Spectrometry
for ID and Prediction
Cris Lapthorn University of Greenwich
Background University of Bath - BSc Chemistry, with industrial year at Pfizer, Sandwich
Pfizer, Sandwich – Team Leader for Open-Access MS, NMR and Separations; >£3M facility
supporting 500,000 samples p.a., ~100 chemists, supervision for 5 FTEs.
Pfizer, Sandwich – Mass spectrometry specialist; supported oligonucleotide, chemical biology &
chemistry projects using high resolution MS techniques, proteomics and chemometrics.
Novartis, Horsham – Analytical Scientist, supported biology and research chemistry.
University of Greenwich - Head of Mass Spectrometry Services; supporting teaching and research
using mass spectrometry and providing consultancy services to external partners.
Thermo Orbitrap XL with FAIMS ion mobility
Waters Synapt G2 with travelling wave ion mobility
Ion mobility adds unique structural
insights to mass spectrometry Mass spectrometry can often quantify using sensitive measurements, and
identify using nominal/accurate mass and elemental composition.
Collision induced dissociation gives some evidence for structure through
product ions.
Ion mobility gives additional separating power on the same timescales as
mass spectrometry with little compromise.
Ion mobility gives rich insights into structure typically investigated by
other techniques including x-ray crystallography or NMR spectroscopy.
Ion mobility spectrometry-mass spectrometry (IMS-MS) of small molecules: Separating and assigning structures to ions
Mass Spectrom. Rev., vol. 32, no. 1, pp. 43, 2013. C. Lapthorn, F. Pullen, and B. Z. Chowdhry
One of the 10 ten most
accessed papers in
Mass Spectrometry Reviews
Overview
1. Evaluation of CCS prediction for small molecules
- initial evaluation, opportunities for improvement
2. MultiMOBCAL – a rapid framework for CCS prediction
- pathways to increased adoption of CCS prediction
3. Evidence from molecular modelling for charge location isomers
- implications for quantitation and utility of IMS
A comparison of theoretical and
experimental CCS for ‘small’ molecules
Geometry optimisation used Gaussian 09 with the
hybrid SCF-DFT B3LYP method and the
6-311++G(d,p) or 6-31G(d,p) basis sets.
Additional keywords pop=(mk,dipole) were used to
generate Merz-Singh-Kollman partial atomic charges
constrained to match the dipole moment.
Collision cross sections were calculated using
Waters Driftscope or Unifi and predicted using
MOBCAL with calculated charge distribution
via projection approximation and trajectory
methods.
How can IMS help in real world problems?
• Build libraries and compare with ‘real’ data
Severine Goscinny - Department of Food,
Medicines and Consumer Safety, Scientific
Institute of Public Health, Belgium,
Mike McCullagh - Waters
How can IMS help in real world problems?
Shimizu, A. & Chiba, M. Ion Mobility Spectrometry–Mass Spectrometry Analysis for the Site of Aromatic Hydroxylation.
Drug Metab. Dispos. 41, 1295–1299 (2013).
CH3CH3
O
NH
N
OH
OH
O-
O
F
OH
CH3
O
OO
OH
OH
M
P
7
O
6
8
Atorvastatin
Warfarin
Parent Compound Potential Metabolites TM-Based Calculated CCS (Å2)
Intact Metabolites N-Methyl Pyridine Derivatives
Atorvastatin O-hydroxy atorvastatin 182.29 200.26
M-hydroxy atorvastatin 188.36 206.61
P-hydroxy atorvastatin 187.73 214.55
Warfarin 6-Hydroxy warfarin 110.42 140.62
7-Hydroxy warfarin 110.23 142.60
8-Hydroxy warfarin 109.84 135.92
ASMS 2015
Investigation of Ion Mobility Mass Spectrometry Analysis of Electrochemically Generated Oxidation Products of Opiates and Comparison with
Theoretical CCS Values
Cris Lapthorn1; Frank Pullen1; Susana da Silva Torres2; Mark R. Taylor2; Russell Mortishire-Smith3; Jayne Kirk3; Andrew Baker4 1University of Greenwich, Chatham Maritime, UK; 2Pfizer, Sandwich, UK; 3Waters Corp, Manchester, UK; 4Waters, Inc., Pleasanton, CA
Predict separation of isomers in impurity analysis, degradation, metabolism, natural products
O P O Cl
Cl
OCH3
OCH3
Dichlorvos
NH
N
S
N
Thiabendazole
CH3
N
N
NH
CH3
Pyrimethanil
CH3 O
NH CH3
CH3
CH3
Ethoxyquin
CH3
CH3
CH3
ClN
N N
OH
Tebuconazole
Cl
N
N
N
S
OF
FF
NH2 Cl
F
F
F
FibrinoprilFlufenoxuron
F
O
NH
O
NH
F
O Cl
F
FF
F
Severine Goscinny - Department of Food,
Medicines and Consumer Safety, Scientific
Institute of Public Health, Belgium,
Mike McCullagh - Waters
How useful is molecular modelling with
ion mobility mass spectrometry? O3
2
OH1
4 5
7
8CH39
CH310
NH26
H5a
pregabalin
OH8
7 1
2 3
4
56
9NH10
CH311
CH312
H7a
H9a
ephedrine
O12
11
NH10
4
3 2
1O7
8CH3965
CH313
phenacetin
CH314
13
6
7
8
9
10
1
2
3
4
5
O11
CH312
15O17
OH16
H13a
naproxen13
12
2
3
15
14
4
5
6
7 8
9
1011
N1
16
17
18
NH19
CH320
desipramine
O18
3NH4
5 O19
NH
12
12
1314
15
1617
6
7
89
10
11
CH320
5-(p-methylphenyl)-5-phenylhydantoin
CH317
O16
12
11
10
15
14
13
O18
CH319
O20CH3
21
9
5
6
N1
2
N3
4
NH28
NH27
trimethoprim
N16
17 22
21
2019
18
13
1415
11
OH12
7
N1
65
4
8
3
9
CH210
2
H11a
H7a
H4a
H3a
cinchonine
O21
S20
O22
NH223
16 17
12
13
O18
CH319
14
15
10
O11
NH9
8
5
N1
6 CH37
2
34
sulpiride
O20
19
25OH26
1
OH18
14
15
34
1312
1110
9O23
8 7
6
CH322
5
17
O24
16
2
CH321
H3a
H4a
H5a
cortisone
NH220
S15
O16
O19 8
9
Cl17
10
5
NH
43
NH2
S1
O11
O12
6
7
13
Cl14
Cl18
trichlormethiazide
Cl27
17
18
19 20
21
16
4
5
6
NH1
2
3
12
O26
O13
14 CH315
7
O8
9
10
NH211
CH325
22
O28
O23CH3
24
amlodipine
O28
23
NH22
21
25
26
18
19
Cl2720
17
16
N13
12
11
N10
3
N2
S1
56
7
89
4
15
14
24
ziprasidone
O12
11
N13
14
15
N1619
N28
27
26
25
O32CH3
33
24
O30
CH331
23
22
21
N20
NH229
17
18
2
O1 6
5
O4
3
10
9
8
7doxazosin CH3
9
N4
3
2
N1
S7
O8 11
12
13
14
O17
18CH319
15 20 N28 27
23 N24
CH330
N25
26
3132
CH333
22NH21
O29
16
O10
6
5
sildenafil
CH311
9
O10
NH8
4
32
1
65
OH7
acetaminophen
CH39
8
NH7
1
23
4
56
n-ethylaniline
CH317
16CH318
NH1514
98
O7
1
65
4
3 2
11
12
CH213
OH10
alprenolol
CH322
N+
4
32
N1
65
7
13
14
15
16
17
12N11
10
9NH818
19
20
21
Cl24
O-
23
clozapine n-oxide
CH313
12
CH321
11
14
15
16
N17
CH318
22
23
24
29
28
27
26
25O30
CH331
O32
CH333
19
N20
5
4
3
2
1
6
O7
CH38
O9
CH310
verapamil
CH331 O
30
18
17
16
15
1419
NH13
12
11
10 9
N1
20
H20a21
4
H4a
3
H3a
2
8
7
H7a
6
H6a
5
H5a22
O32
O23
CH324
O25 CH3
26
O27
28
O29
33
34
3536
37
38O43
CH344
O41
CH342
O39
CH340
reserpine
CH320
2
N3
45
N1
6
7
8
9
10
1413
19 18
17
1612
N11
CH321
15
O22
ondansetron
CH32
N1
CH334
NH8
NH5
6
NH9
NH27
metformin
*
*
n=23
How does experimental CCS fit with
theoretical CCS?
Conclusions • A large ‘small’ molecule dataset comparing
experimental vs theoretical CCS using He(g) and
N2(g) MOBCAL has been evaluated
• There is a very good agreement between
experimental and theoretical CCS, typically within ~
2% CCS or 2 x experimental error
• Provides a key dataset for tuning, learning about
deviations from good agreement.
An automated pipeline for calculating CCS.
Why, how and when?
open source tool open source tool open source tool
collaboration w/ commercial package self written
Rapid CCS prediction for all
MultiMOBCAL
- Runs on multiple PCs, 1 instance is 3-7x faster
- Queues calculations so can run unattended
- Summarises important CCS from verbose MOBCAL OUT files
- Results can be synchronised through shared drives, Dropbox etc
- Predictions can run 10-100 times c.f. manual workflows
Online molecular modelling
Access to molecular modelling typically requires either
dedicated personnel or significant training and infrastructure
(high powered computing and software).
Future accessibility might be enabled by cloud-based
services e.g.
1. Schrodinger recently docked 1.8million compounds on a
600 core CycleCloud Condor cluster.
2. Accelerys Pipeline Pilot is now available on BT’s BT for
Life Sciences cloud computing platform.
3. Chorus now can store, share and visualise data online
using Amazon Web Services.
Can a molecular modelling service provide fee-for-
service molecular modelling?
01MAY12_CL2.raw:1
01MAY12_CL2.raw : 1
LC-MS ion chromatogram [MH]+ for Norfloxacin (m/z 320)
Ion mobilogram [MH]+ for Norfloxacin (m/z 320)
Charge location isomers in
fluoroquinolone antibiotics
Species 1 Species 2
Ion mobilogram [MH]+ for Norfloxacin (m/z 320)
• Fluoroquinolones are a class of antimicrobial
agents administered to livestock to
(a) prevention and control of infections, and
(b) growth promotion.
• Due to the resistant microorganisms in the
human population, the F.D.A. introduced a
ban on the use of enrofloxacin and
ciprofloxacin in livestock production in
September, 2005.
• The use of antibiotic growth promoting
agents (AGPs) in animal husbandry has been
forbidden in the European Union (EU) since
2006, when the final four antibiotics were
banned as growth promoters.
• EU Maximum Residue Levels (MRLs)
currently exist for eight (fluoro)-quinolone
compounds ranging from 10 to 1900 μg kg-1
dependant on the species and tissue type.
F
N N
NH
+
H
O
O
OH
CH3
singly protonated on piperazine
singly protonated on carboxyl
-H2O
F
N N
NH
O
O+
CH3
-CO2
F
N N
NH
+
H
O
CH3
m/z 302
m/z 320m/z 320
1211
109
8
F17
7
1615N
14
13
21
N1
2
3
NH4
5
6
O1819
O23
OH20
CH322
H
F
N N
NH
O
OH
O+
CH3
MSMS of
Species 2
MSMS of
Species 1
Protomer 1 Protomer 2
norflaxin 600 40
m/z200 205 210 215 220 225 230 235 240 245 250 255 260 265 270 275 280 285 290 295 300 305 310 315 320 325 330 335 340
%
0
100
m/z200 205 210 215 220 225 230 235 240 245 250 255 260 265 270 275 280 285 290 295 300 305 310 315 320 325 330 335 340
%
0
100
m/z200 205 210 215 220 225 230 235 240 245 250 255 260 265 270 275 280 285 290 295 300 305 310 315 320 325 330 335 340
%
0
100
01MAY12_CL2_peak3_RTandDTselected 66 (3.510) Cm (66:68) 1: TOF MSMS 0.00ES+ 8.76e4276.1530
233.1090
219.0966256.1427234.1103
320.1400
277.1555321.1489
01MAY12_CL2_peak2_RTandDTselected 57 (3.024) Cm (57:59) 1: TOF MSMS 0.00ES+ 3.27e4302.1311
320.1400
303.1339
321.1411
01MAY12_CL2_peak1_RTandDTselected 55 (2.916) Cm (53:55) 1: TOF MSMS 0.00ES+ 4.50e3276.1530
233.1090
256.1497
302.1311
277.1555 320.1400303.1339
Does molecular modelling predict IM-MS for protomers (I)?
Experimental
Qualitatively observe nr. baseline resolution of m/z 320 species in norfloxacin (R~1.5)
Experimental CCS (eCCS) for different species is ~11Å2 different
Structure tCCS eCCS
Theoretical
Theoretical CCS (tCCS) from projection approximation calculations predicts small
differences in CCS.
Can ion mobility mass spectrometry and density functional theory help elucidate protonation sites in ‘small’ molecules?,
Rapid Commun. Mass Spectrom., vol. 27, no. 21, pp. 2399, 2013. C. Lapthorn, T. J. Dines, B. Z. Chowdhry, G. L. Perkins, and F. S. Pullen
Does molecular modelling predict IM-MS for protomers (II)?
Theoretical
Theoretical CCS (tCCS) from trajectory method calculations correctly predicts
significant differences in CCS
Bordoli Prize
Conclusions
1. Projection approximation calculations
demonstrate for these protomers the IMS
separation does not appear to be based on
physical area presented to buffer gas.
2. Molecular modelling and trajectory
method calculations demonstrate for these
protomers that the charge distribution are
significantly different and the difference in
CCS is correctly predicted, but the absolute
CCSs require improvement
Synapt G2-Si Ionkey Exp.
CCS (Å2) in N2(g) Theo. CCS (Å2) in N2(g)
% Diff (Theo. vs Synapt
G2-Si Exp.)
Norfloxacin
N4 186.0
193.6 4.0%
O18 171.4
180.8 5.4%
Fluoroquinolones N2 @ 20mL/min 200/180V
Time-0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00 3.20 3.40 3.60 3.80 4.00 4.20 4.40 4.60 4.80 5.00 5.20 5.40 5.60 5.80 6.00 6.20 6.40 6.60 6.80 7.00 7.20 7.40 7.60 7.80
%
0
100
-0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00 3.20 3.40 3.60 3.80 4.00 4.20 4.40 4.60 4.80 5.00 5.20 5.40 5.60 5.80 6.00 6.20 6.40 6.60 6.80 7.00 7.20 7.40 7.60 7.80
%
0
100
-0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00 3.20 3.40 3.60 3.80 4.00 4.20 4.40 4.60 4.80 5.00 5.20 5.40 5.60 5.80 6.00 6.20 6.40 6.60 6.80 7.00 7.20 7.40 7.60 7.80
%
0
100
MP102414_008 2: TOF MS ES+ 360.125_360.2
4.22e5
4.20
MP102414_008 2: TOF MS ES+ 332.109_332.13
3.76e5
4.04
3.73
MP102414_008 2: TOF MS ES+ 319.984_320.177
4.76e5
4.00
3.69
Enrofloxacin
Ciprofloxacin
Norfloxacin
N2 – medium polarisability
better separation
He – low polarisability
no discernible separation
Linear Exp. CCS (Å2) in
N2(g) Synapt G2-Si Ionkey
Exp. CCS (Å2) N2(g)
% Diff (G2-Si Ionkey vs
Linear D.T.) Norfloxacin
N4 187.4 186.0 0.8% O18 172.3 171.4 0.5%
12 11 10
9
8
F17
7
16
15N14
13
21
N1
2
3
NH4
5
6
O18
19
O23
OH20
CH322
Norfloxacin• Increased separation of two
major components of
fluoroquinolone precursor m/z
in more polarisizable gases in
the order CO2>N2>He
• Results are consistent in
travelling wave and drift tube
ion mobility regimes
• Theoretical calculations are
consistent with experimental
findings. Charge distribution,
plays major role in
differences in CCS.
Conclusions
Charge location isomers have now been demonstrated
1) Using both positive and negative ionisation modes
2) For a range of (bio)chemical classes inc. simple acids, steroids,
fluoroquinolone antibiotics, pesticides and porphyrins
3) With complementary evidence from molecular modelling, product ion
spectra and action spectroscopy
The existence of charge location isomers has often been uniquely revealed using
ion mobility.
• Where are the rest?
• How can we utilise IMS to improve quantitative performance?
ASMS 2015
The importance of charge isomers in quantitation; ion mobility mass spectrometry of fluoroquinolone antibiotics
Cris Lapthorn1; Mike McCullagh2; Sara Stead2; Martin Palmer2; Kevin Giles2; Keith Richardson2; Jasper Boschmans3; Frank Sobott3; Frank Pullen1; Babur
Chowdhry1; George Perkins4 1University of Greenwich, Chatham Maritime, UK; 2Waters Corp, Manchester, UK;3University of Antwerp, Antwerp, Belgium; 4149 Hickory Corner Road,
Milford, NJ
Acknowledgements Prof Frank Pullen – University of Greenwich
Dr Mike McCullagh - Waters
George Perkins – Sanofi Pasteur, USA
Prof Babur Chowdhry – University of Greenwich
Patricia Wright - University of Greenwich
Prof Trevor Dines – University of Dundee
Dr Jiayun Pang – University of Greenwich
Yanira Ruhe - University of Greenwich
Dr Alex Muck – Waters
Dr Jonathan Williams – Waters
Dr Keith Richardson – Waters
Dr Jeff Brown – Waters
Prof Bela Paizs – University of Bangor
Prof Perdita Barran – University of Manchester
Severine Goscinny - ISP-WIV, Belgium
Scott Rudland – Waters
Alex Hunt – Waters
Dr Grigoriy A. Andrienko – Chemcraft