Advantages and Limitation of Hydrogen/Deuterium

Exchange with Mass Spec. Detection (H/DX-MS) in

Conducing Higher Order Structural Comparability

Studies on Protein Therapeutics

Steven Berkowitz, Principal Investigator

Biogen Idec

1st International Symposium on Higher Order Structure of

Protein Therapeutics

Sept. 26, 2011

Uses of H/DX-MS in Developing Biopharmaceutical

Research

Find the Right Target Modifier

“Drug”

Make and modify via “Intelligent

Design”?

a. Structure-function

b. Epitope mapping

c. Mechanism of action

d. Stability

Process Development

Make a commercially viable drug

Process changes, consistency of

manufacturing, drug variants

a. Comparability/characterization

b. Formulation/stability

c. Impact of primary structure

changes (PTMs) on conformation

d. Silent (non-covalent) changes in

conformation

2

Polypeptide chain

Amide hydrogen

(fraction of a sec

to days –108)

Side chain exchangeable

hydrogen (very rapid

exchange)

Non-exchangeable

hydrogen

Types of Hydrogens Present in Proteins (in Terms of Their Ability to Exchange)

3

Engen & Smith (2001). Anal. Chem. 73, 256A-265A.

Wales & Engen (2006). Mass Spectrom. Rev. 25, 158-170.

(Amide) H/DX-MS: Continuous labeling Experiment

H’s at backbone amide

positions

D2O

(1:10 to 1:20)

H’s & D’s at backbone amide

positions

Structural Information is Inferred from Data Acquired on the

Amount and Rate of Hydrogen Exchange (HX) – By Simply Measuring the

Change in Mass Using MS

A) Take samples at

different times & stop

(slow) exchange by

lowering temp. & pH

B) Measure mass

change via MS

4

Because Conformation Effects HX

0

1

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4

5

6

7

0.01 0.1 1 10 100 1000

Time (min)

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0.01 0.1 1 10 100 10000

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0.01 0.1 1 10 100 1000

Deu

teri

um

co

nte

nt

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0.01 0.1 1 10 100 10000

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Time (min)

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0.01 0.1 1 10 100 10000

1

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Deu

teri

um

co

nte

nt

Global Exchange Comparison of Two Intact

Biopharmaceutical Samples

Sample #1

Sample #2 (variant form of sample #1)

5

Label, sample,

stop reaction by

lowering

temperature & pH

MS (mass change

in peptides) Digest (pepsin)

Local H/DX-MS (Bottom-Up Approach)

*Wales, T.E., et al.(2008). Anal Chem. 80, 6815-6820

Injector Pepsin-column RP-column MSLC

+

Sample Handling

Robotics

*Waters’ Synapt HDMS system

Nano-Acquity H/DX Synapt G1

(UPLC) Interface box (MS)

6

Robot –sample

handling/injector

Nano – Acquity

UPLC

H/DX-MS

Box

Mass Spec

Synapt

Waters Commercial Prototype H/DX-MS System

7

The Dynamic World of Proteins (Folding-Unfolding)

8

Is This the Correct Picture of a Protein Structure?

Not Completely! 9

H/DX-MS represents the first practical tool to assess this information on a routine basis

10

Very important role:

1) Folding

2) Stability

3) Interactions, e.g.

a. Catalysis

b. Signaling

c. Recognition

d. Assembly (Agg.)

H/DX-MS Comparability Studies with Interferon -1a (IFN)

1 11 21 31 41 51

MSYNLLGFLQ RSSNFQCQKL LWQLNGRLEY CLKDRMNFDI PEEIKQLQQF QKEDAALTIY

61 71 81 91 101 111

EMLQNIFAIF RQDSSSTGWN ETIVENLLAN VYHQINHLKT VLEEKLEKED FTRGKLMSSL

121 131 141 151 161

HLKRYYGRIL HYLKAKEYSH CAWTIVRVEI LRNFYFINRL TGYLRN

3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0

Time (min)

Re

lati

ve

Ab

un

da

nc

e Undeuterated

10 seconds

1 minute

10 minutes

60 minutes

240 minutes

3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0

Time (min)

Re

lati

ve

Ab

un

da

nc

e Undeuterated

10 seconds

1 minute

10 minutes

60 minutes

240 minutes

996 998 1000 1002 1004 1006 1008

m/z

996 998 1000 1002 1004 1006 1008

m/z

• MW ~23kD

• 1 N-linked glycan

• 1 free -SH

• 167 residues

• Sequence coverage > 94% 11

Data Analysis and Display Problem MSYNL

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R3 R2

R3

MSYNLLGF

0

1

2

3

4

5

6

7

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

SYNLL

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

NLLGF

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LGFLQRSSN

0

1

2

3

4

5

6

7

8

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

GFL

0

0.5

1

1.5

2

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

FLQRSSN

0

1

2

3

4

5

6

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

FLQRSSNF

0

1

2

3

4

5

6

7

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

FQCQKL

0

1

2

3

4

5

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

QCQKL

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LWQLNGRL

0

1

2

3

4

5

6

7

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LWQLNGRLEY

0

1

2

3

4

5

6

7

8

9

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LWQLN(deam)GRL

0

1

2

3

4

5

6

7

8

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

QLNGRL

0

1

2

3

4

5

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LNGR

0

0.5

1

1.5

2

2.5

3

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LNGR

0

0.5

1

1.5

2

2.5

3

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

KDRMNFDIPEE

0

1

2

3

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5

6

7

8

9

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

KDRMNFDIPEEI

0

2

4

6

8

10

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

NFDIPEE

0

1

2

3

4

5

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

FDIPEE

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

DIPEE

0

0.5

1

1.5

2

2.5

3

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

DIPEEIKQLQQ

0

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8

9

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

DIPEEIKQLQQFQKEDAAL

0

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4

6

8

10

12

14

16

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

IKQLQQ

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5

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Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

IKQLQQFQKE

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Time (min)

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R1 R2

R3

IKQLQQF

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Time (min)

Rela

tive D

eute

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Level

(Da)

R1 R2

R3

IKQLQQFQKEDAAL

0

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6

8

10

12

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

LQQFQKEDAAL

0

2

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6

8

10

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

FQKEDAALT

0

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4

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6

7

8

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

FQKEDAAL

0

1

2

3

4

5

6

7

0 1 10 100 1000

Time (min)

Rela

tive D

eute

rium

Level

(Da)

R1 R2

R3

….

12

Amino Acid Sequence

Each peptide is equally spaced along the x-axis in the order determined by each peptide’s

midpoint position in the Protein’s Linear Sequence relative to the N – terminus

1 2 4 5 6 7 8 9 3 10

Alternative Mode of Displaying & Comparing

H/DX-MS Data

…

…

Graphic x-axis

13

Graphic x-axis = quasi-sequence representation of protein

Converting H/DX-MS Comparison Data to a Single Plot Using “Relative” Fractional Exchange, F(i,t) = (Mi,t change)/[#AA in Peptide “i” – (#Proline + 1)]

Peptide “i” exchange plot Ref & Exp, step 1 Top plot Ref Bottom plot (Exp) ( -1), step 2

Transpose data points to y-axis, step 3 Transfer peptide “i” data to correct x position, step 4

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0

Log (time, min)

Fra

cti

on

al

Ex

ch

an

ge

, F

(i,

t)

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0

Log (time, min)

Fra

cti

on

al

Ex

ch

an

ge

, F

(i,

t)

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0

Log (time, min)

Fra

cti

on

al

Ex

ch

an

ge

, F

(i,

t)

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

0 10 20 30 40 50 60 70

Peptide Positon, i

Fra

cti

on

al

Ex

ch

an

ge

, F

(i,

t)

14

H/DX-MS: Comparison of 2 Different IFN Lots

Made Under Different Tissue Culture Growth Conditions

)(MS)(MS)MD( ti,expti,refti,

5

1t

ti,s )MD((i)D

Standard Culture Media

New Culture Media

T = 0.17 min

T = 1 min

T = 10 min

T = 60 min

T = 240 min

15 -1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0

Log (time, min)

Fra

cti

on

al

Ex

ch

an

ge

, F

(i,

t)

Mass Difference, Da, Data

Types of Peptide HDX-MS Exchange Profiles (Mass

Difference vs Time) and Their Impact on Ds(i)

16 Morgan CR, Engen, JR, Current Protocol Protein (2009) Nov.; doi:10.1002/0471140864.ps1706s58

H/DX-MS Mass Difference Display Format

17

)(MS)(MS)MD( ti,expti,refti,

5

1t

ti,s )MD((i)D

T = 0.17 min

T = 1 min

T = 10 min

T = 60 min

T = 240 min

H/DX-MS Mass Difference, Da, Display Format

(continued)

18

Uncertainty (SD) in H/DX-MS D(Mi,t) Data Points

19

Uncertainty in (H/DX-MS) Mass Difference Measurements

20

Average Standard Deviation in D(Mi,t) 0.14 Da s

Uncertainty in D(Mi,t) at a given % confidence limit (%CL) = t%CL, df [s/(n)0.5]

Where:

t%CL, df = Student t factor for a give % confidence limit and number degrees of freedom (df = n-1)

s/(n)0.5 = Estimate of the standard error in the mean value for any D(Mi,t) based on “n”

measurements

5

1t

ti,s )MD((i)D

Uncertainty in Ds(i) (over all 5 time points) obtained from simple propagation of error analysis

98% confidence limit for D(Mi,t) determined from n = 3 measurements 0.5 Da

98% confidence limit for Ds(i) determined from n = 3 measurements 1.1 Da

1. For peptide “i” one D(Mi,t) data point must exceed the 0.5 Da limit

and the Ds(i) value for the that peptide must also exceed 1.1 Da limit.

2. If one D(Mi,t) data point exceeds 0.5 Da limit, but the Ds(i) value for

that peptide does not exceed 1.1 Da limit, recalculate the value for

Ds(i) by summing the absolute (abs) differences

3. If Ds(i)abs exceeds the 1.1 Da limit, the two peptide “i” are not

non-comparable. However, if this new sum does not exceed the 1.1

Da limit, flag this peptide pair for manual review and assessment.

5

1t

ti,abss )]Mabs[D((i)D

Criteria for Assessing Difference in Conformation

21

H/DX-MS Mass Difference Display

22

98% CL in D( Mi,t)

98% CL in Ds(i) Difference Indices

67

1i

s 1.1)(i)](abs[DDI(1)67

1i

5

1t

ti, )5.0)]M(abs[D(DI(2)

Quantitative “Difference Indices”

DI(1) = 0

DI(2) = 0

DI(1) = 0

DI(2) = 0

H/DX-MS: Comparison of 2 Different IFN Lots Made Under Different

Tissue Culture Growth Conditions, Average of 4 Different Runs

IFN, standard growth conditions

IFN, experimental growth conditions

T = 0.17 min

T = 1 min

T = 10 min

T = 60 min

T = 240 min

23

Separate Mass Difference Plots of Each of the Four H/DX-MS Runs

24

Mass Difference Plot for the Same IFN Sample Run on

Different Days (1 Run of Each Sample)

25

H/DX-MS: Comparison of IFN vs Alkylated (NEM) IFN (Average of 3 Exp.)

DI(1) = 92

DI(2) = 67

T = 0.17 min

T = 1 min

T = 10 min

T = 60 min

T = 240 min

26

H/DX-MS: Comparison of IFN vs Oxidized (H2O2) IFN, (Average of 3 Exp.)

T = 0.17 min

T = 1 min

T = 10 min

T = 60 min

T = 240 min

DI(1) = 187

DI(2) = 143

27

Alkylated IFN has very poor biological activity

while

Oxidized IFN is fully or nearly fully active!

However, both have very poor stability

(Aggregation)!

28

-8

-6

-4

-2

0

2

4

6

8

0 5 10 15 20 25 30 35 40 45 50

Dif

fere

nc

e (

Da

)

FIX vs FIX+Ca2+

Gla EGF Catalytic

29

FIX vs the FIX part of FIX-Fc

-8

-6

-4

-2

0

2

4

6

8

0 5 10 15 20 25 30 35 40 45 50

A

Dif

fere

nce

(D

a)

-8

-6

-4

-2

0

2

4

6

8

0 5 10 15 20 25 30 35 40 45 50

B

Dif

fere

nce

(D

a)

FIX with Ca2+ vs the FIX part of FIX-Fc with Ca2+

Peptide Number, i

30

DI(1) = 0

DI(2) = 0

DI(1) = 0

DI(2) = 0

Heavy chain Light chain

Pepsin Mapping of an Intact Mab

> 95 % sequence coverage

1 11 21 31 41 51 61

EVQLVESGGG LAKPGGSLRL SCAASGFRFT FNNYYMDWVR QAPGQGLEWV SRISSSGDPT WYADSVKGRF

71 81 91 101 111 121 131

TISRENAKNT LFLQMNSLRA EDTAVYYCAS LTTGSDSWGQ GVLVTVSSAS TKGPSVFPLA PSSKSTSGGT

141 151 161 171 181 191 201

AALGCLVKDY FPEPVTVSWN SGALTSGVHT FPAVLQSSGL YSLSSVVTVP SSSLGTQTYI CNVNHKPSNT

211 221 231 241 251 261 271

KVDKKVEPKS CDKTHTCPPC PAPELLGGPS VFLFPPKPKD TLMISRTPEV TCVVVDVSHE DPEVKFNWYV

281 291 301 311 321 331 341

DGVEVHNAKT KPREEQYNST YRVVSVLTVL HQDWLNGKEY KCKVSNKALP APIEKTISKA KGQPREPQVY

351 361 371 381 391 401 411

TLPPSRDELT KNQVSLTCLV KGFYPSDIAV EWESNGQPEN NYKTTPPVLD SDGSFFLYSK LTVDKSRWQQ

421 431 441

GNVFSCSVMH EALHNHYTQK SLSLSPG

1 11 21 30 41 51

DIQMTQSPSS LSASVGDRVT ITCRASQDIR YYLNWYQQKP GKAPKLLIYV ASSLQSGVPS

61 71 81 91 101 111

RFSGSGSGTE FTLTVSSLQP EDFATYYCLQ VYSTPRTFGQ GTKVEIKRTV AAPSVFIFPP

121 131 141 151 161 171

SDEQLKSGTA SVVCLLNNFY PREAKVQWKV DNALQSGNSQ ESVTEQDSKD STYSLSSTLT

181 191 201 211

LSKADYEKHK VYACEVTHQG LSSPVTKSFN RGEC

31

Important Attributes & Future Opportunities in Using

H/DX-MS in the Biopharmaceutical Industry

1. High spatial resolution – at present a few AAs, may reach 1AA with ETD!!

2. High sequence coverage

3. Can detect a very small change in a large molecule

4. Requires little material – sub-nanomoles/entire experiment! – variant analysis

5. Redundancy via overlapping sequences helps validate data

6. Reasonably good sample throughput – via robotic automation

7. Good reproducibility within a given day

8. Can provide routine kinetic (temporal) information about structural dynamics

9. Can conduct experiments under wide range of conditions

10. Can conduct experiments in the presence of other components

11. Ion mobility separation within MS – help deal with complex mixtures

12. Gas HX within MS (sub-millisecond dynamics) – assess side chain HX 32

Challenges in Using H/DX-MS in the Biopharmaceutical

Industry

1. Further reduction in data analysis time is needed via computer automation! Days

to minutes!

2. Develop an effective & compact mode for presenting data – data display

3. Presently, the ability to detect small protein populations that have a structural

element change in its conformation is not that low (population needs to be ~20-

40% or greater to detect) – can we improve?

4. Improve long term reproducibility

5. Interference effects – sample matrix

6. Only one commercial instrument exists

7. New scientific capability & information – What do we do when we see low

level of difference(s)? What’s important, What isn’t?

33

Speaker Would Like to Thank and Acknowledge the

Following People:

Dr. John Engen and members of his group (Northeastern Univ.)

Staff at Waters

Dr. Igor Kaltashov and members of his group (UMass, Amherst)

Special Thanks to Dr. Rohin Mhatre (Biogen Idec)

Damian Houde

34