D - Marc-André Delsuc`s

Transcription

Measuring molecular interactions using
NMR spectroscopy
Marc-André Delsuc
CEUM 2012
Golden Sands - Bulgaria
vendredi 1 février 2013
Measuring Diffusion by NMR
z
I
= exp(−Dq 2(∆ − δ/3))
Io
O
y
x
q = γGδ
90°
G
!
180°
G
q : pitch of the magnetization helix
"
DOSY spectrum
variation - of q
- of Δ
Laplace analysis
by MaxEnt
• CEUM 2012 - Golden Sand •
60
DOSY spectrum of a Simple Sugar Mixture
10e2,6
Mean
heavier species
10e2,2
damping
10e2,4
Diff. coeff.
10e2,8
10e3
10e3,2
lighter species
10e3,4%
20
40
Mean
ppm
5,4
5,2
5
4,8
4,6
•
solution analysis
•
no separation - no gradient concentration
•
NMR analytical power (1D - (2D) ..)
4,4
4,2
4
3,8
3,6
3,4
3,2
%
50
100
sugar mixture
500
sugar mixture
dosy _161 (DOSY 1H)
400
dosy _150 (DOSY 1H)
dosy _142 (DOSY 1H)
dosy _130 (DOSY 1H)
Glucose
300
MEAN F2 (DOSY 1H)
200
Sucrose
100
Raffinose
ß-cyclodextrine
%
0
mixture
point
1!400
1!600
1!800
2!000
2!200
2!400
2!600
2!800
3!000
3!200
Laplace is not Fourier !
sum of two exponental decays
with
x2 ratio in damping constants (D)
same intensities
Mono-dispersity and Poly-dispersity
 Mono-dispersity
 Poly-dispersity
Laplace spectrum
 Laplace Transform
δ
δ
S
S
 Inverse Laplace Transform
MaxEnt and Inverse Laplace Transform (ILT)
• Direct ILT is not possible, it is an
unstable operation
• MaxEnt permits to realize a true
ILT with no hypothesis on the size
nor the number of constituants
asymmetric distribution
0.01
0.1
10
1
D
4 lines
• No constraints on gradient
intensity values
0.01
0.1
• some examples :
1
2 close lines
10
100D
 100 data points
 0.1% Gaussian noise
 3000 Iterations
0.1
Delsuc and Malliavin. Maximum entropy
processing of DOSY NMR spectra.
Anal Chem (1998) 70 pp. 2146-2148
1
10
D
receiver gain for both the sample spectrum and the ERETIC
signal (Fig. 2). An initial power level of 20 dB was used for
sampling all diffusion profiles of the ERETIC signal (Eqn (2)). For
continuous distributions, the convolution product for the intensity
attenuation of the ERETIC signal was numerically calculated over
64 points, equally spread in the diffusion coefficient D dimension
(range 10−7 to 10−11 m2 /s), assuming normal distributions along
the diffusion coefficient dimension (Eqn (6)). Figure 2 shows an
excellent agreement between the experimentally determined
output intensity attenuation and the calculated input one using
a diffusion coefficient of 1 × 10−10 m2 /s. Consequently, possible
systematic errors introduced by the implementation of ERETIC
technique in the DOSY methodology can safely be excluded.
Comparison of methods
Research Article
Received: 9 May 2008
Revised: 17 July 2008
Accepted: 28 July 2008
Published online in Wiley Interscience
(www.interscience.com) DOI 10.1002/mrc.2315
ERETIC implemented in diffusion-ordered NMR
as a diffusion reference
Luk Van Lokeren,a∗ Rainer Kerssebaum,b Rudolph Willema and
Pavletta Denkovaa,c∗
The ERETIC (Electronic Reference To access In vivo Concentrations) technique generates an electronic signal in the NMR
spectrometer which is detected simultaneously to the sample FID during the acquisition. The implementation of the ERETIC
sequence in any 2D DOSY experimental scheme enables one to generate directly into the raw 2D DOSY spectrum a reference
signal with an attenuation simulated to describe a well-defined diffusion behavior. This simulated intensity attenuation can be
used to evaluate the output generated by any DOSY data treatment algorithm, in a single as well as multichannel approach and
provide insight into their precision, accuracy, scope and limitations. The ERETIC sequence implemented in the standard bipolar
pulsed field gradient longitudinal eddy current delay (LED) sequence is illustrated on various algorithms presented previously
in the literature for the analysis of the generated ERETIC–DOSY spectra of simulated model systems representing discrete and
c 2008 John Wiley & Sons, Ltd.
continuous diffusion profiles in mono- and bi-Gaussian diffusion regimes. Copyright !
Data processing
To reduce calculation time, the raw 2D DOSY NMR data were first
processed in the F2 dimension by standard Fourier Transform,
combined with a moving average algorithm reducing the number
of data points in F2 dimension from 16 to 2 K, without window
function. To extract the diffusion dimension, the complete data
set representing the signal attenuation as a function of the NMR
scattering vector q2 (q = γ δG), both for ERETIC and chemical
• calibration using eretic signal as reference
Keywords: NMR; 1 H; DOSY; ERETIC; least squares; maximum entropy; CONTIN; MCR
Introduction
In diffusion-ordered NMR spectroscopy (DOSY NMR), the chemical
shift scale is combined with a diffusion coefficient scale in
order to obtain a so-called 2D DOSY spectrum displaying crosspeaks correlating chemical shifts – usually of protons – with the
diffusion coefficient of the molecules they arise from. For this
reason, DOSY NMR is a powerful technique for the analysis of
complex mixtures, allowing molecules to be discriminated from
differentiated diffusion regimes.[1 – 6] Since, at least in a spherical
model, the diffusion coefficient is related to the particle size by the
law of Stokes-Einstein,[7 – 9]
• compared
alternative multichannel algorithms – direct exponential curve
resolution algorithm (DECRA),[1,26,27] multivariate curve resolution
(MCR)[28,29] and component resolved NMR (CORE[30] and SCORE[31] )
fit globally all resonances and provide spectra of all the
components, ideally those of the pure compounds. These methods
usually give different results, e.g. for complex multicomponent
systems in which discrete or continuously distributed diffusion
coefficients are present. Some DOSY processing methods produce
good component discrimination when well-resolved diffusion
peaks are available (SPLMOD, DISCRETE, LS), while others (CONTIN)
are suitable for analysis of samples displaying a continuous
distribution of the diffusion coefficients.[1,32 – 34] As a result, a
combination of several methods is often needed to achieve
complete and reliable sample characterization. Keeping scope and
limitations of DOSY data analysis methods in mind is therefore
essential for selecting the optimal processing strategy to match
the properties of the system.
Two main approaches, using either simulated data or calibration
mixtures, can be used to test the accuracy and precision of
DOSY processing schemes. Regarding multichannel methods,
Nilsson and Morris emphasize the importance of correcting
systematic errors during CORE processing.[30,31] Antalek developed
• Least Square (Nilsson implementation)
rH =
kB T
cπ ηD
(1)
• MCR (Nilsson implementation)
where rH is the hydrodynamic radius, D the diffusion coefficient of
the particle, η the viscosity of the sample, c a size parameter, kB
the Boltzmann constant and T the absolute temperature, species
with different sizes and/or molar masses (e.g. dendrimers,[10]
polymers,[11] macromolecules[12] and micelles[13] ) are discriminated. The potential to investigate interactions in chemical
systems[14 – 16] enables one to probe association/dissociation
equilibria and their kinetics (hydrogen bonding, macroclusters,
nanoparticles, micelles).[17 – 19]
Theoretical aspects of pulsed field gradient NMR and solutions
to reduce or avoid possible practical problems[5,6] as well as
methodology to optimize DOSY experiments are available.[1,3]
Yet, processing DOSY NMR data remains far from straightforward.
2013
Th
di
do
sp
pr
am
m
by
fr
pr
w
or
di
gr
w
no
si
th
va
ov
cu
w
FI
of
w
re
R
G
Th
of
Figure 2. Simulated (input, continuous line) and experimental (output,
!) intensity attenuation of the ERETIC resonance simulated with
D = 1 × 10−10 m2 /s. The inset shows the 1D 1H NMR spectrum, clearly
showing the ERETIC resonance at −2 ppm having an intensity of the same
order of magnitude as the other resonances in the spectrum.
w
di
D
is
• CONTIN (Bruker implementation)
• MaxEnt (Gifa implementation)
vendredi 1 février
∗
Correspondence to: Luk Van Lokeren, Department of Materials and Chemistry
(MACH), High Resolution NMR Centre (HNMR), Vrije Universiteit Brussel,
Pleinlaan 2, B-1050 Brussels, Belgium. E-mail: [email protected]
Pavletta Denkova, NMR Laboratory, Institute of Organic Chemistry with Centre
of Phytochemistry, Bulgarian Academy of Sciences, Acad. G. Bontchev Str., Bl.9,
1113 Sofia, Bulgaria. E-mail: [email protected]
Magn. Reson. Chem. 2008, 46, S63–S71
c 2008 John Wile
Copyright %
Din
Dout
fout
Dout
fout
Dout
fout
Dout
fout
hosen on the basis of the results presented in Table 4 and the
1.00
1.14
0.45
–
–
0.48
1.13
0.45
sults are
compiled
into Tables
5 and
6 1.02
respectively.
The value
of
0.32
0.55
0.38
1.00
0.33
0.52
0.11
0.55
−10 0.37
2
m /s is the highest value below which the two signals
5 × 10
1.00
1.29
0.38
1.93
0.03
0.71
0.52
2.90
0.57
e well0.40
resolved
both0.50
the molar
and the
0.48 and
0.62
0.97 fractions
0.43
0.48
0.57 diffusion
0.43
oefficients
still determined
high3.16
accuracy
1.00 are
0.75
1.00
– with
– a relatively
0.90
0.37
0.53by
= 2 ×0.65
10−100.47
m2 /s
least one
the system
0.50 algorithm,
–
–while0.50
1.00 with
0.92 σin0.63
representative for the case where both parameters are poorly
etermined for all algorithms.
The diffusion profiles calculated by MaxEnt of the system
ith relatively narrow distribution width (σin = 0.5 × 10−10 m2 /s,
able 5) as a function of the molar fractions of the two components
e presented in Fig. 7. For the system with narrow distributions
n both diffusion regimes, resulting in the two component signals
eing well separated, a satisfactory accuracy for both diffusion
oefficients and molar fractions for both components is obtained
y MaxEnt (deviation less than 10%) as long as both molar fractions
e larger than 10%. As already mentioned for mono-Gaussian
ontinuous systems, no conclusions can be made considering
e width of the diffusion coefficient distributions generated by
ngle-channel algorithms.
1.00 0.70 0.98 0.85 0.77 0.32 0.89 0.84
"
0.10 0.30 0.10 0.15
#0.06 0.68
$2 % 0.12 0.16
1 D − Ds,in
ff,in
fs,in
1.00
! 1.06exp0.94
− 0.88 0.74 0.95
+ ! 0.95
A(D) =0.90
2
σ
2
2
σf,in
0.10 0.102π σ0.11
0.06 0.08 s,in 0.26 0.12 2π0.05
s,in
% 0.81 0.97 0.98
1.00 0.95 " 1.05# 0.98 $
0.90
2
1 D − Df,in
exp −
0.10 0.05
0.09 0.02 0.06 0.19 0.11 0.02
2
σf,in
Working with polydisperse samples
• Two discrete components
Figure 5. Diffusion profiles for discrete two component systems: (A)
0.81
0.05
4.38
0.73
0.98
(8)
0.13
0.88
0.12
0.88
0.12
0.82
0.18
• Two broad components
Analogously to the discrete distribution, we first investigated
a continuous distribution of two well-separated components of
equal population and diffusion coefficients that differed by one
order of magnitude. The best results are obtained with the MaxEnt
algorithm and the respective diffusion profiles calculated upon
systematic increase of the distribution width are presented in
Fig. 6. The results of the variation of the distribution width, σin are
collected in Table 4.
Figure 7. Diffusion profiles for a two component system with narrow
Table
Output
diffusion coefficients (109 Dout9.4;
m2(C)
/s) −
and
logfractions
Din = 9
− 5.
log D
in = 9 and 9.5; (B) − log Din = 9 and
9
continuous distribution of diffusion coefficients (Din = 1 × 10−9 and
calculated
different
algorithms
referred
the input
10 Din
(fout )and
9.3 in 0.50by
molar
fraction.
The two vertical
linesto
in each
graph indicate
1 × 10−10 m2 /s, σin = 0.5 × 10−10 m2 /s), determined for different molar
valuetheand
theDininput
− log
values.fraction fin for a two component system with
fractions of the two components using MaxEnt.
a narrow continuous distribution of diffusion coefficients (Din =
−9
−10
2
−10
2
1.00 × 10 and 1.00 × 10
m /s, σin = 0.5 × 10
m /s)
In some actual chemical mixtures, the diffusion coefficients are
CONTIN
MCR
well separatedLS(micelles-free
molecules,MaxEnt
monomers–polymers).
The
resultsprofiles
summarized
in Table 6,
representing
a two comFigure
6. Diffusion
for a two component
system
with continuous
However,
in
most
samples,
the
difference
between
diffusion
Din
fThe
Dout
fout
Dout combined
fout
Doutwithfout
Dout NMR
fout allows
ERETIC
technique
2D DOSY
oneofsystem
todiffusion
conclude
that
ILT-MaxEnt
enables
one
to 10
−9−10
in
distribution
coefficients
around
the input
values
=21×10
×
m2 /s),
ponent
with
a broad
distribution
(σinDin=
coefficients
much less pronounced.
So, we
decreased
−10 m2 /s, with
achieve isa satisfactory
discrimination
limit
betweenthe
diffusion
coefficients
andmolar
a high
fraction-sensitivity,
even highand the
and 1×10
fraction
0.50, as a function of the...
distribution
demonstrate
that
in
this
case
the
diffusion
coefficients
1.00 difference
0.05 0.38
0.25
0.82
0.01
0.68
0.12
3.27
0.92
both
diffusion
for asignificantly
50/50 bi-Gaussian
width values,
σin , given
in the respective profiles, as obtained with MaxEnt.
noise between
levels, up
to 15%,
doregimes
not affect
the numerical
value
deviations.
fractions of the two diffusing species are calculated with unsatisorder0.08
to determine
the discrimination
0.10 diffusion
0.95 decay
0.08 in
0.75
0.99 0.10
0.88 0.09 limit
0.08
factory accuracy (deviation more than 10%) for all algorithms and
the method.
1.00 (Table
0.103) of0.48
0.27 Since
1.01 MaxEnt
0.01 has
0.87the best
0.15 discrimination
2.25 0.77
these0.73
diffusion
Fig. 5. 0.23
For
all fractions. The diffusion profiles calculated
MaxEnt for this sys2 /s)by
0.10 limit
0.90only0.08
0.08 profiles
0.99 are
0.10shown
0.85 in 0.09
Table 4. Output diffusion coefficients (109 Dout m•
and fractions
CEUM
2012 - Golden Sand •
) = 0.5,
a factor
of 3.16,
diffusion
as a function
of thealgorithms
molar fraction
two components
are
by different
referredof
to the
the input
109 Din
(ftem
out ) calculated
1.00 !(log
0.30 Din0.87
0.39i.e. 1.04
0.03
1.03 the0.34
0.87 profile
0.90
calculated
MaxEnt shows two well-resolved Gaussians with
value
and theininput
fin case
for a two
system
vendredi
1 févrierby
2013
presented
Fig. fraction
8. In this
the component
diffusion peak
forwith
thea slower dif-
Comparison of methods
ERETIC-DOSY as a diffusion reference
• Linearity
Table 1. Diffusion coefficient calculated (Dout ) by different algorithms
referred to the input Din value, as a function of the noise level,
Din = 1.00 × 10−9 m2 /s
L. Van Lokeren et al.
Noise
(%)
pulse
(3)
(4)
.[45,47]
ected
nction
(5)
ts the
ented,
thms,
utions
fusion
ained
fusion
ent, as
LS
(10−9 m2 /s)
CONTIN
(10−9 m2 /s)
MaxEnt
(10−9 m2 /s)
MCR
(10−9 m2 /s)
1.10
1.13
1.12
1.18
1.07
1.03
0.96
0.76
0.83
1.03
1.01
1.04
1.05
1.06
1.01
1.00
1.00
1.00
1.02
0.99
0
3
7
11
15
Table 2. Diffusion coefficient calculated (Dout ) by different algorithms
referred to the input Din value, as a function of the input distribution
width, σin , Din = 1.00 × 10−9 m2 /s
σin
(10−10 m2 /s)
0.00
0.50
2.00
3.00
LS
(10−9 m2 /s)
CONTIN
(10−9 m2 /s)
MaxEnt
(10−9 m2 /s)
MCR
(10−9 m2 /s)
1.10
1.10
1.07
1.02
1.03
1.01
0.96
0.91
1.01
1.01
0.96
0.99
1.00
1.00
0.87
0.72
Figure 3. Diffusion coefficient calculated (Dout , logarithmic left ordinate) by
LS (◦,•), CONTIN (!,"), MaxEnt (♦,$) and MCR (%, &) as a function of
the input Din value of the ERETIC signal. Data simulated with ! = 50 ms,
δ = 2 ms are presented
withare
open
symbols and
the attenuation
level,
The results
summarized
in Table
2.
expressed as a percentage
of the
full Gaussian
attenuation
is
The results
presented
in Table
2 show amplitude
that the accuracy
of
indicated by × the
(rightcalculated
ordinate), diffusion
for which coefficient
100% attenuation
is
achieved
is good for a distribution
−9
−10
2
for Din values ofwidth
only σ3.16up
× 10
and
1
×
10
−10
2 m /s. Data simulated
to 2.00 × 10
m /s, except for MCR, but tends
with ! = 100 ms, δ = 8inms are presented−10
with closed
and the
2 /s for symbols
m
CONTIN
and again MCR.
to
be
worse
at
3.00
×
10
attenuation level is indicated by +, for which it is 100% for all Din values.
Hence,
therethe
is no
significant
between a discrete
The dotted straight
linesince
represents
ideal
Dout = Ddifference
in line.
and a continuous diffusion coefficient distribution, diffusion NMR
provides a satisfactory strategy for the investigation of molecular
Din values with
errors e.g.
of less
than or
5%
for CONTIN,
MaxEnt and
systems,
polymers
polydisperse
nanoparticles,
where such
continuous
distribution
of diffusion
is tobe
be expected
MCR. LS is lessaaccurate
with
errors around
10%,coefficients
but it should
[48]
a priori.
mentioned that
LS can be dependent on the initial values given
for the algorithm.[22] The excellent results for the multichannel
MCRSimulating
are of major
importance
since
MCR has the power
multiple
diffusion
regimes
vendredi 1algorithm
février 2013
(a)
(b)
Figure 4. Output diffusion coefficients (Dout , a) and associated output
molar fractions (fout , b) as a function of the input molar fractions fin for a
discrete two component system with input values Din = 3.16 × 10−9 and
1.00 × 10−10 m2 /s. Full symbols correspond to the Din = 3.16 × 10−9 m2 /s
value and its associated fin , while open symbols correspond to the
Din = 1.00 × 10−10 m2 /s value and its corresponding fin : LS (◦,•), CONTIN
(!,"), MaxEnt (♦,$) and MCR (%,&). The dotted horizontal straight lines (a)
represent the two Din values, while the oblique dotted lines (b) represent
the two fin = values.
AMD Opteron 2.5 GHz
8775
Tests run on 1 processor. Depending on the type of processor the return time is quite fluctuating
(1.7 factor from Quad Core Intel Xeon X5570 and AMD Opteron 2.5GHz). Processing time plotted
according to the number of processors used. Job run on 1850 columns at runlevel 5.
Solving the time pb : RDC
with
Marie-Aude Coutouly
NMRTEC
Tests
performed on multiprocessor workstation, on 1850 columns, at level 5.
Correcting for instabilities - Sophora
• slow fluctuation
• observed
- due to change in room temperature
- oscillation reproduces A/C regulation loop
• D2O lock
- strong temperature dependence of water chemical shift
are strongly dependent of the acquisition conditions and of the overall system stability. In fact, perturbations which are sometimes
invisible in the direct dimension can lead to poor quality DOSY spectra.
Sophora
A new method, called SOPHORA [1] («SOPHisticated Optimization by spectral ReAlignment») is used to correct for spectrometer
imperfections or mis-adjustments. This method works as follows : first, a peak picking is done on a small spectral region (containing one
signal) of each 1D row. The chemical shift of this signal in the first row is used later on as the reference. Then, for each raw, the shift
from the reference is estimated. Finally, this shift is corrected by shifting the whole spectrum, using the method described in [2] for
shearing.
SOPHORA is available as a macro running under the NMRnotebookTM software [3].
• Important for DOSY quality
Temperature regulation issues
No correction
Sugar Mixture
Using SOPHORA
Heating due to strong gradient pulses
O Assemat, MA Coutouly, R Hajjar, MA Delsuc Validation of molecular
mass measurements by means of Diffusion-Ordered NMR Spectroscopy;
Application to Oligosaccharides. Cr Chim (2010) 13 pp. 412-415
Accurate diffusion
coefficient
value
• CEUM
2012 - Golden Sand •
Heating due to intense gradients
Sugar Mixture
• Important when measuring
large
molecules
Using SOPHORA
Heating due to strong gradient pulses
Accurate diffusion coefficient value
No correction
Avoid artifacts
Using SOPHORA
PEG
1. O. Assémat, M.A. Coutouly, R. Hajjar, and M.A. Delsuc, submitted.
2. D. Tramesel, V. Catherinot, M.A. Delsuc, J. Magn. Reson. 188 (2007) 56
3. NMRTEC, http://www.nmrtec.com/software/nmrnotebook.html
Analytical Service, Expertise & Development
2. Results and discussion
stimulated echo with bipolar pulse pair was used to dephase
the nuclear magnetization and rephase it after the diffusionencoding delay (D) [10,12]. The p/2 pulses after the bipolar gradients transferred magnetization on the z-axis, thus reducing T2
relaxation, and allowing spoiler gradients (G1 and G2) to be applied. A LED delay was incorporated between the BPPSTE and
the final ES pulse sequence [3]. 2D spectra were obtained by
incrementing the gradient strengths on a series of 1D experiments and by fitting the experimental signal attenuation to the
Stejskal–Tanner equation
Water suppression
2.1. NMR sequence
Basic pulse sequences PGSE and PGSTE are two different approaches for diffusion measurement by NMR based on magnetization coherence during diffusion time. A variant of PGSTE, using a
bipolar gradient pulse pair, reduced the effect of inhomogeneous
background gradients [10] and the insertion of a supplementary
• Excitation sculpting
• selective pulses and additional gradients for water suppression
Fig. 5. 1H 1D projections of the black tea infusion 2D DOSY-ES spectrum for different increments (12 (A), 13 (B), 14 (C), and 15 (D)) corresponding to gradient field strengths
Fig. 1. BPPSTE-ES pulse sequence.
Narrow
wide
bars represent
/2 gradient
and pduration
pulses,
respectively.
To excite
narrowest
spectral
region,
, respectively.
Bipolar pulse p
field
is 1.5
ms with a sineshaped
format.the
The 1D
spectrum (C)solvent
corresponds
to the distorted
FID. selective 180! squareof 9.6, 10.2, 10.9,
and 11.6and
G cm-1
This FID suffered
from ADC and
overload
due to the
unsuppressed
Thisdepend
distorted on
all resonances
in theunder
spectrum
and made
them appear
less intensedelay
that of 3 ms and a LED (s)
were applied
centered
atintense
4.7 ppm.
The Dsolvent
and dsignal.
values
the mixture
study.
A gradient
recovery
shaped pulses of 1000 ls length
they would otherwise be.
!1
of 10 ms were used. The spoiler gradients G1 and G2 were 1 ms long, with a field strength of !7.92 and !6.09 G cm , respectively. G3 and G4 for the ES sequence were 1 ms
long, with a field strength of 14.33 and 5.08 G cm-1, respectively. The diffusion-encoding gradient G0 was used from 5 to 95%, with the gradient system previously calibrated
to 46.25 G cm-1 at maximum
Phases were x unless indicated. Phase cycles were /1 = x, x, !x, !x; /2 = 4x, 4(!x), 4(y), 4(!y); /3 = x, !x, x, !x, !x, x, !x, x, y, !y, y, !y,
Tableintensity.
1
1
H 1Dx,
projections
Principal
coherence transfer
pathways
for
the
pulse
and!y,
10! flip
errors
different
increments
corresponding
/5 magnetization
= 16(!x), 16(!y);
/6 = !x
and /
=BPPSTE-ES
x, !x, !x,
x,sequence
!x, x, for
x, 1!
!x,
y, angle
y, !y,
y, for
!y,
!y, y,
!x, x, x,
!x, x, !x,to !x,
y, !y, !y, y, !y, y, y, !y.
!y, y, !y, y; /4 = 16x, 16(y);
rec
• requires fine tuning of the gradients
shown in Fig. 5
Grad
1! Error
10! Error
Maxt I
Pathway
Maxt I
Pathway
9.6
0.52
(1,!1,0,1,!1,0,!1,!1,!1)
10.2
10.9
—
1.04
—
(1,!1,0,1,0,!1,!1,!1,!1)
11.6
—
—
0.78
0.42
3.10
1.06
10.11
0.23
(0,0,0,1,!1,0,!1,0,!1)
(1,!1,0,1,!1,0,!1,!1,!1)
(1,!1,0,1,0,1,0,!1,!1)
(0,!1,0,1,!1,!1,!1,!1,!1)
(1,!1,0,1,0,!1,!1,!1,!1)
(0,0,0,1,0,1,0,0,!1)
Grad, gradient field strengths in G cm!1.
Maxt I, maximum estimated intensity of the water artifact signal.
10.9 G cm!1V.Gilard,
was the only Y.Prigent,
one showing a M.Malet-Martino
strong spurious water sigS.Balayssac, M.A-Delsuc,
nal, which comes from a coherence transfer pathway where magJ.Magn.Reson (2009)
196goes
p78to the z-axis after the second 180! pulse and is
netization
excited to !1 quanta by the fourth 90! pulse. This pathway is significantly populated for a 10! flip angle error (10.11 in Table 1), and
be used in the DOSY-ES set-up procedure to build a diffusion gradient list devoid of gradients producing unwanted echoes.
3. Conclusions
RS<)7*$C77E! &7=*D%($! HLbJ! .%&! C$$)! '&$1! =7(! &>$,*(%!
%)%0?&3&B!!
Water suppression
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
L
NMR spectrum
of a black tea
e! MN4OG64!
RS<! &>$,*('#!
7=!infusion
%! C0%,E! *$%! 3)='&37)! ($,7(1$1! %*!
X3FB! "B!DOSY-ES
recorded at 298K (10% D2O,
• CEUM 2012 - Golden Sand
< pH 5.2).
"KIh! 8LUc! M"N-! >e! bB"9B! $>3F%007,%*$,.3)! F%00%*$-! #$>3F%007,%*$,.3)-!
vendredi
0 1 février 2013
(
'
•
0*#$9!')-4$27!4*!4!&'1'&'$%'J!)2!&4$9'!1&2(!D":,L!dJ!/-#7'!
#)!/4*!#$!)-'!&4$9'!D":Db!d!12&!MPb!472$'!FDXH;!!
Water suppression
!
!
)
)
)
)
)
)
)
)
)
)
)
)
) NMR spectrum, recorded at 297K, of the human salivary
DOSY-ES
D at 70 µM with 12 equivalents of epigallocatechin gallate
proteinc;!
IB5
<#9;!
E! >?@A:B@! UVW! *5'%)&0(J! &'%2&8'8! 4)! ,XLZJ! 21! )-'! -0(4$!
*47#N4&6!5&2)'#$!MPb!4)!L`!"V!#$!E,?e>,?!+X`eD`.!/#)-!D,!'R0#N47'$)*!21!
S.Balayssac, M.A-Delsuc, V.Gilard, Y.Prigent, M.Malet-Martino
'5#94772%4)'%-#$!
c`!
J.Magn.Reson
(2009) 196 p78 94774)'! +BfOf.! 4$8! D``! (V! 21! U4O7! +5E! ";b.;!
• CEUM 2012 - Golden Sand
9&48#'$)!#$%&'('$)*!/'&'!4%R0#&'8!#$!D,Y!*%4$*J!/#)-!4!8#110*#2$!)#('!21!
•
GPC calibration kits from Fluka
with
Lionel Allouche
D=539 µm2/s
238 Da
D=65 µm2/s
12.1 kDa
D=14 µm2/s
209 kDa
Mean
10e0.5
damping
10e1
10e1.5
10e2
10e2.5
%0
50
100
150
sum (DOSY 1H/1H) D2O 600MHz
Row 1 (DOSY 1H)
ppm
3.7
3.65
3.6
3.55
3.5
3.45
3.4
%
20
40
60
%
0
20
40
60
80
100
120
140
MEAN F1 (DOSY 1H) D2O 600MHz
damping
10e0,5
10e1
10e1,5
10e2
10e2,5
10e3
Diffusion - Diffusivity - hydrodynamic radius
• Stokes-Einstein equation
• relates D to hydrodynamic radius
• the radius of the sphere that diffuses with the
same coefficient “the molecule that we will
imagine as a sphere of radius rH” *
depends on T,
η , etc..
kT
D=
6πηrH
RH
• hardly a real measure of the molecular volume
• Diffusivity is defined as a relative to a
reference molecule
• independent on the conditions
★
A.Einstein Annalen der Physik (4) 19 (1906) p288
D
Dr =
Do
PolyEthyleneOxide in D2O
• series of PEO
• from monomer to Md
D∝M
1
y = 5,0133 * x^(-0,5388) R= 0,99889
• 4 orders of magnitude !
(
2
Diffusion relative to D O
•
very different from 1 / 3
(Stokes-Einstein)
−α
)
n
0,1
1 / 1.86
0,01
S Augé, PO Schmit, CA Crutchfield, MT Islam, DJ Harris,
E Durand, M Clemancey, AA Quoineaud, JM Lancelin, Y
Prigent, F Taulelle, MA Delsuc
J.Phys.Chem 113 p1914-18 (2009)
0,001
100
1000
10
4
10
5
10
6
Molecular Mass
series of globular proteins
§ globular proteins
§ 4kDa to 120kDa
200
§ standard conditions
D∝M
−α
y = 3412,3 * x^(-0,37203) R= 0,98131
Diffusion in µm^2/s
§ 23°C
§ 3 mg/ml
§ 1mM Tris, as diffusivity reference
fractal dimension
1
dF =
α
100
90
80
70
60
1 / 2.56
50
40
S Augé, PO Schmit, CA Crutchfield, MT Islam, DJ Harris,
E Durand, M Clemancey, AA Quoineaud, JM Lancelin, Y
Prigent, F Taulelle, MA Delsuc
J.Phys.Chem 113 p1914-18 (2009)
30
10
4
Molecular Mass in D
10
5
some Theory
• Flory theory of soluble polymers
• Rg
Radius of Gyration
Rg = kM
1
dF =
δ
δ
dF
1.0
rigid rod
1.67
2.0
polymer in Theta solvent
3.0
polymer in poor
solvent
Flory, P. University Press (1953).
Schimmel, P. R. & Flory, P. J. (1967) PNAS 58, 52–59.
fractal dimension
dF
3.0
3.0
2.5
2.0
2.0
Flory-predicted zone
for unrestriced polymers
dF = 2
Θ conditions
dF = 5/3
1.5
1.0
1.0
fractal dimension
3.0
3.0
2.5
2.0
2.0
1.5
Flory-predicted zone
dF
POMs clusters
Globular proteins
1
α=
dF
PS in toluene
PS in acetone
PolySaccharides
PEO in water
DNA
denatured peptides
PS in THF
Da
≈
Db
�
Mb
Ma
�α
1.0
1.0
Verifying the relation for spherical molecules
with
Francis Taulelle
Na2[Mo3S4(Hnta)3].5H2O (3), Cs2 [Mo10O10S10(OH)10(glu)].11H2O (4), Rb2
[Mo12O12S12(OH)12(H2O) (Muco)].21H2O (5), Cs2[Mo12O12S12(OH)12(TerP)].
12DMF 0.2H2O (6), (NMe4)2[Mo12O12S12(OH)12(H2O)3(TMT)].17H2O (7), K3
[Mo12 O12S12(OH)12 (Trim)].22H2O (8), Rb4[Mo16O16S16(OH)16(H2O)2 (IsoP)2].
28H2O (9), Li4[Mo16O16S16 (OH)16(H2O)4(PDA)2].20H2O (10), Cs5[Mo18O18S18
(OH)18(H2O)9(Mo3S4(nta)3)].36H2O (11), K9[Mo18O18S18(OH)18(H2O)9(Mo3S4
(nta)3)][Mo2O2S2(nta)2].36H2O (12),
(NH4)42[Mo132O372(H2O)72(CH3COO)30],
300H2O,10CH3 COONH4, (13), Rb2[Mo12O12S12(OH)12(H2O) (Adip)].11H2O (14),
K2[Mo12O12S12(OH)12(Sub)].28H2O (15), Rb3(NMe4)[Mo12O12S12 (OH)12(H2O)2
(Succ)2].11H2O (16), and (NMe4)2[Mo14O14S14 (OH)14(H2O)3(Azel)].29H2O (17)
S Floquet, S Brun, JF Lemonnier, M Henry, MA Delsuc, Y Prigent,
E Cadot, F Taulelle. Molecular weights of cyclic and hollow
clusters measured by DOSY NMR spectroscopy.
J Am Chem Soc (2009) 131 (47) pp. 17254-9
Figure 1. Structural representations of compounds used in the present study
Verifying the relation for spherical molecules
dF = 1 / 2.96
Figure 3. Correlation between diffusion and mass of clusters. Red dots represents ring or
hollow polyanions without exchange (1 to 13). Inset: representation of the power law between
diffusion and mass of the clusters, with 95% interval plot as dotted lines.
Figure 4: Correlation between the estimated radii of clusters from their crystallographic
description (see text) and the diffusion deduced radii of clusters with the
hydrodynamic diameter from the Power law and Stokes-Einstein relation. The slope is
1.021 ± 0.062 with a correlation coefficient of 0.965.
S Floquet, S Brun, JF Lemonnier, M Henry, MA Delsuc, Y Prigent,
E Cadot, F Taulelle. Molecular weights of cyclic and hollow
clusters measured by DOSY NMR spectroscopy.
J Am Chem Soc (2009) 131 (47) pp. 17254-9
sugar mixture
10e2,8
Da
≈
Db
10e2,7
Glucose
MW = 201 +/- 43
Mb
Ma
�α
10e2,6
2 - 342
Sucrose
10e2,5
Raffinose
MW = 357 +/- 76
3 - 504
MW = 500 +/- 105
4 - 666
10e2,4
5 - 828
ß-cyclodextrine (MW =1135)
6 - 990
MW = 1040 +/- 219
7 - 1152
10e2,3
damping
1 - 180
�
ppm
5,2
5
4,8
4,6
4,4
4,2
4
O Assemat, MA Coutouly, R Hajjar, MA Delsuc Validation of molecular
mass measurements by means of Diffusion-Ordered NMR Spectroscopy;
Application to Oligosaccharides. Cr Chim (2010) 13 pp. 412-415
polynucleosomes
Cell
260
Figure 1. The Atomic Structure of the Nucleosome Core Particle
Each strand of DNA is shown in different shade of blue. The DNA makes 1.7 turns around the histone octamer to form an overall particle w
a disk-like structure. Histones are colored as in (A) and (B) of Figure 2.
karyote, appearing in some cases directly adjacent to
assembled (Figures 1, 2A, and 2B). Each histone us
the centromeres. A 73 base pair unit from the !-satellite
a protein fold, the histone fold, consisting of a thre
Khorasanizadeh.
The
nucleosome:
fromdomains
genomicform
organization
region of the human X chromosome has successfully
helix
core
domain. These
“handshak
http://www.humans.be/images/biocell/chromatine.jpg
to genomic
Cell (2004)
vol. 116
(2)give
pp. rise
259-72
been used to produce a 2-fold symmetric DNA
palin- regulation.
arrangements
(see Figure
2B) to
to the heter
drome that could then be reconstituted with separately
dimer H2A-H2B and the heterodimer H3-H4 (Arents
prepared histone octamers for high resolution structure
al., 1991). Biochemical studies have shown that in so
determination (Harp et al., 1996).
tions of moderate salt and in the absence of DNA, t
There are currently a handful of high-resolution strucH3-H4 complex forms a tetramer whereas H2A-H2
• 2B
tures of the nucleosome core particles available all of
complex remains•aCEUM
stable2012
dimer- Golden
(FiguresSand
2A and
which contain the DNA palindrome derived from the
These components then associate together further
human !-satellite DNA (Figure 1). A 2.8 Å resolution
form the histone octamer in the presence of DNA or
polynucleosomes
with
Bruno Kieffer
Christian Koehler
Lionel Allouche
Valine signal
CHO cell polynucleosomes, mild digestion - overnight acquisition on a 600MHz with DOTY probe
polynucleosomes
CHO cell polynucleosomes, stronger digestion vendredi 1 février 2013
nucleosomes
CHO cell polynucleosomes, harsh digestion
D NMR
D = 1.11 % 103 lm2 s"1.
It should be noted that the measure relies on the complete measurement of all the different polymers present in the sample. In
consequence, the PFG experiment should be designed to allow a
signal attenuation from the longest chains, sufficient for a correct
measurement of their diffusion coefficient. In the present case, all
experiments have been performed in the same conditions, optimized on the largest monodisperse polymer studied. However,
Determining polydispersity
he 1D-1H NMR spectrum of mix L is shown in Fig. 1. Very few
s are observed and are easily assigned. Besides the resonance
7 ppm of the principal chain, other resonances are observed.
different spin systems can be identified. The signal A correds to the chain methylene group, and the signal B to the pen-
• typical PEO 1H spectrum
mixture of controlled
polydispersity
Here PDI = 2.12
integral ratio
provides mean chain
length
13C
1
satellites
13C
Fig. 1. 1D- H NMR spectrum of a poly-ethyleneoxide in D2O, mix L. Assignment is given in inset, D and E are the
J Viéville,
M Tanty, MA Delsuc
Polydispersity index of polymers revealed by DOSY NMR.
J Magn Reson (2011) 212 pp169
satellites
13
C satellites of A.
looking to diffusion profiles
difference in behaviour
Mix
Mix
Mix
Mix
Fig. 2. Log-plot of the observed decays for varying gradient values squared for mix
L. Diamonds are from the signal of the main chain (signal A Fig. 1), dots are from the
signal of the extremity (signal C).
when the composition of the mix is unknown, one should use large
enough PFG intensities to ensure the signal attenuation of the
heaviest polymers. As a rule of thumb, a final attenuation around
10% on a monodisperse species is usually required to permit a precise determination of the diffusion coefficient. Thus, when studying an unknown polydisperse polymer, one should try to reach at
least a 1% attenuation for the main signal.
• all signal evolutions are non-linear
• end groups appear lighter!
L
M
N
O
19.1
21.4
22.4
13.5
19.4
24.8
23.8
13.9
2.51
3.3
3.41
5.23
2.24
2.41
2.75
4.48
858.5
961.7
1001.7
611.3
853.6
1091.2
1047.2
611.6
Mega-dalton polymers have already been pre
on standard spectrometers [3]. So, the main siz
the application of this technique is the possibility
signals from the chain extremities. Of course, this
to achieve on large polymers, as the extremity sign
faint to be observed. This was done here for PEO
10 kDa, despite the fact that this signal only integ
The method requires that the extremity of the p
an isolated signal in the NMR spectrum. This cond
J. Viéville et al. / Journal of Magnetic Resonance 212 (2011) 169–173
Table 1
Experimental results compared to theoretical values.
PDI
N
PEO
mix
Main chain
End groups
Fig. 2. Log-plot of the observed decays for varying gradient values squared for mix
L. Diamonds are from the signal of the main chain (signal A Fig. 1), dots are from the
signal of the extremity (signal C).
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
Mix
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
Mn (g mol!1)
Mw
Theo
Exp
Theo
Exp
Theo
Exp
The
36.3
49.4
107.5
8.7
8.8
23
71.5
44.8
34.7
38.1
15.7
19.1
21.4
22.4
13.5
36.1
53.7
120
8.7
9.5
23.8
85.3
47.5
37
39.8
15.9
19.4
24.8
23.8
13.9
1.04
1.07
1.11
1.12
1.14
1.26
1.28
1.34
1.54
2.01
2.12
2.51
3.3
3.41
5.23
1.06
1.08
1.12
1.12
1.17
1.31
1.28
1.15
1.5
2.2
1.89
2.24
2.41
2.75
4.48
1615
2190
4750
400.6
403.4
1021
3165
1989.3
1544.3
1696.9
710.3
858.5
961.7
1001.7
611.3
1588.4
2362.8
5280
382.8
418
1047.2
3753.2
2090
1628
1751.2
699.6
853.6
1091.2
1047.2
611.6
167
234
527
447
459
126
405
251
238
323
133
200
306
332
309
Fig. 3. 2D-DOSY spectrum of mix L. The black rectangle on the right is the region over which the integration is made to determine hDni. hDwi is determine
the whole spectral range shown by outer red rectangle. (For interpretation of the references to color inCEUM
this figure
legend,
reader Sand
is referred to the
2012
- the
Golden
article.)
Mega-dalton polymers •have already been precise
•
on standard spectrometers [3]. So, the main size li
ð1Þ
chain is equal to the product of its length
meric unit M, the average molecular mas
are given in Eqs. (3) and (4),
polydispersity index
the molecule, M its mass and
tal dimension is a measure of
lvent, and is equal to the inw
1/m. It is comprised between
M
P DI =
Mn
P
ni Mi
Mn ¼ P
¼ NM
ni
P
P
2
mi Mi
ni Mi
Mw ¼ P
¼P
mi
ni M i
GNMR measurements has alknown
to
lead
to
non
expoMn averages by the number of molecules
where ni is the number of molecules of m
spersity
[8]. Thebyanalysis
of of matter
Mw averages
the amount
ecules of mass Mi, and N the averaged ch
use of Inverse Laplace TransMn and Mw are statistical features of t
tion but with different weightings. Becau
So does the DOSY measure
tique et de Biologie Moléculaire et
End groups averages by the number
of molecules
=>than
Dn or equal to Mn, and
always
greater
ies, BP 10142, 67404 Illkirch cedex,
Main chain averages by the number
monomer
orofequal
to 1.=> Dw
NMR parameters are also obtained as
[email protected] (J. Viéville),
�
�−dmeasured
F
.-A. Delsuc).
whole
sample.
Signals
from
t
M
<D >
r Inc. All rights reserved.
P DI =
w
Mn
=
w
< Dn >
let’s take an example
n
M
D
12
12
0.5
10
10
0.6
8
8
0.7
6
6
0.8
a polydisperse mixture of four
polymers
<Mn> = (12+10+8+6)/4 = 9.0
<Mw> = (122+102+82+62)/36 = 9.56
<Dn> = (0.5+0.6+0.7+0.8)/4 = 0.65
<Dw> = (10*0.5+8*0.6+6*0.7+4*0.8)/28 = 0.614
PDI = 1.06
experimental results
J. Viéville et al. / Journal of Magnetic Resonance 212 (2011) 169–173
dF = 1.96
dF = 1.86
dF = 1.76
rves for the average chain length N (left) and the PDI (right). Red lines correspond to theo = exp. The PDI was computed with the fractal dime
; df = 1.96 (upper bar); and df = 1.76 (lower bar). (For interpretation of the references to color in this figure legend, the reader is referred
from integrals
J Viéville, M Tanty, MA Delsuc
from DOSY
nal for the extremity of the studied polymer to be
PEO samples,
the small shift of 0.08 ppm obPolydispersity index of polymers revealed by DOSY NMR.
However this condition is not stringent,
as- Golden
it was
he chain
andReson
the (2011)
extremity
signals, is sufficient
• CEUM 2012
Sandeasily
•
J Magn
212 pp169
here in the case of PEO, where only 0.08 ppm separates
en
this1 février
shift
difference, two different diffusion
vendredi
2013
the formation of complexes between the copper catalyst and the IL
moiety can hinder the purification process of the resulting
Dynamic Article Links <
product.17,25,26
In this paper, we show how the side chain hydroxy moieties of
poly(hydroxyethyl acrylate) (PHEA) polymers27 could be convenientlyCite
replaced
by bromine
groups,
using a mild and efficient
this: Polym.
Chem., 2012,
3, 2723
substitution reaction. Thus, it is possible to obtain quantitatively
www.rsc.org/polymers
the corresponding
polybrominated polymer with minimal synthetic
effort and complete absence of side-products. Furthermore, we
efficient
bromination
of poly(hydroxyethyl
acrylate) and its use
report,Mild
from and
the resulting
polybrominated
structure
used as a
towards
containing
common
scaffold,ionic-liquid
the straightforward
synthesispolymers†
of various IL
polymers, through yield-efficient quaternarization (Scheme 1).
Vinu Krishnan Appukuttan, Anais Dupont, Sandrine Denis-Quanquin, Chantal Andraud and Cyrille Monnereau*
Although similar approaches have already been proposed in the
10
Received
June 2012,
2012
literature,
we29th
think
that Accepted
the one19th
weJuly
introduce
in this communi10.1039/c2py20462b
cation DOI:
presents
many advantages in terms of simplicity, efficiency
and convenience that make it a beneficial alternative to existing
protocols.
To illustrate
versatility
of allows
the methodology,
we 21,22 However, the direct controlled polymerization of IL
electrolytes.
An original
and mild the
bromination
protocol
a polymonomers is not trivial, because of the previously mentioned
acrylate)
ATRP to be pyridine,
chose (hydroxyethyl
to work with
four polymer
differentsynthesized
types ofbynucleophiles:
Polymer
Chemistry
C
COMMUNICATION
tolerance limitation of CP, and it has been reported that the use of
IL monomeric entities can dramatically reduce the polymerization
efficiency and kinetic control. Consequently, to date, reports dealing
with the CP of IL-monomers, are still relatively scarce.23–26 In
particular, ATRP of IL monomers often results in poorly
Synthesis of functional polymers by controlled polymerizations
controlled structures, unless very specific conditions are used, and
(CPs) is an important issue in modern polymer science, since it
the formation of complexes between the copper catalyst and the IL
makes it possible to obtain structures which are otherwise inacmoiety can hinder the purification process of the resulting
cessible by conventional polymerizations.1–3 However, most
product.17,25,26
controlled polymerizations are very sensitive to environmental
In this paper, we show how the side chain hydroxy moieties of
conditions, and thus show moderate tolerance to a number of
poly(hydroxyethyl acrylate) (PHEA) polymers27 could be convefunctional groups.4 To overcome this limitation, post-modification
niently replaced by bromine groups, using a mild and efficient
of polymers obtained by CP appears to be an appealing alternasubstitution reaction. Thus, it is possible to obtain quantitatively
5,6
tive. In this context, poly(halide)polymers (halide ¼ Cl, Br, I) are
the corresponding polybrominated polymer with minimal synthetic
interesting platforms towards more functionalized structures, as
effort and complete absence of side-products. Furthermore, we
halides can be efficiently involved in substitution reactions with a
report, from the resulting polybrominated structure used as a
variety of nucleophiles.7,8 In particular, substitution with ternary
common scaffold, the straightforward synthesis of various IL
amine or phosphine derivatives allows access to ionic-liquid (IL)
polymers, through yield-efficient quaternarization (Scheme 1).
containing polymeric structures, as recently exemplified by Gu and
Although similar approaches have already been proposed in the
Lodge using RAFT polymerization methodology,9 and by Tang
literature,10 we think that the one we introduce in this communi10
et al. using a post-modification sequence on 1,2-polybutadiene.
cation presents many advantages in terms of simplicity, efficiency
SchemeHowever,
1 Synthesis
and bromination
of PHEA monomers
(top) and isits quarterpolymerization
of halide containing
and convenience that make it a beneficial alternative to existing
precluded
in
ATRP,
because
of
the
obvious
possibilities
of
side
nization reaction for the preparation of various IL polymers (bottom).
protocols. To illustrate the versatility of the methodology, we
reactions.11
chose to work with four different types of nucleophiles: pyridine,
ILs have been of widespread
use
in
the
world
of
chemical
Polym. Chem., 2012, 3, 2723–2726 | 2723
vendredi 1 février
2013
synthesis
for two decades as substitutes for classical solvents,12 but
converted readily and quantitatively into its corresponding poly(bromoethyl acrylate) analogue. We show that the latter can be used
as a common precursor towards ionic-liquid containing polymers.
Bromination scheme of PHEA
and its precursor!P1 (Fig. 1). Interestingly, TMSBr had rarely been
reaction proceeded with various degrees of succ
used as a brominating agent in previous literature,29,30 although it
tions of the reactions: no reaction at all occurre
appeared to operate veryn efficiently
and
cleanly
our1Dcase,
as
probably because of too low a nucleophilic ch
(average)
= 22
fromin1H
spectrum
n
proven by the fact that only
a trace amount
of starting material or
With pyridine (P3) and phosphonium (P4
PDI=1,27
from
GPC
side-products are observedPDI=1,23
in the 1H from
and 13DOSY
C NMR spectra of P2
occurred within 48 h, but the conversion was in
(Fig. 1 and ESI†). The IR spectrum showed a decreased intensity of
thily, attempts to improve the conversion efficien
the 1065 cm"1 band, characteristic of C–OH elongation vibrations,
nucleophile in the reaction after the initial 48 h
and a new band at 550 cm"1 which corresponds to the tabulated
microwave activation at higher temperature,
value for the C–Br band (ESI†). As expected, the PDI of P2
expected results; we presume that the kine
calculated from GPC analysis in similar conditions as for P1, was
substitution can be severely hindered in the cour
in the same range as the PDI of its precursor (1.15), thereby
the increased charge density and steric crowdin
showing that no cross-linking reaction occurred to a significant
chain, which is likely to affect the nucleophil
extent during the reaction.
conversions could not be determined from th
because of a severe overlap of broadened peaks.
tentatively attributed to a contamination by
Signals from the extremities show a slightly higher diffusion coefficient...
which is a very well known issue for IL cont
Table 1 Structural characteristics of P1–5
However, it could be roughly estimated that a co
75–85% was obtained in the case of P3, whereas
Molecular weight
P4. Interestingly, after several weeks of agein
much less assumption
By NMR
By GPC
polymer P3, it could be noticed that extra pe
thanspectrum,
in GPCof which the nature will be
NMR
a
PDI
Mn
PDI
Polymer
% Functionalization
Mn
contrast,default
conversion of the side chain bromide us
1H spectrum shows an integration
a nucleophile
P1
100%
5000
17 000
1.12whileas DOSY
•no
calibration
of the 1.11
aromatic
signals
showswas estimated at over 99% for
P2
>99%
7800
1.06
12 000
1.15
the
complete
clearance of
the signal
of the
carbo
•no
molecular
model
(only
dF)
a
mixture
of
the
expected
polymer,
the
P3
75–85%
11 000
1.04
—
—
the Br in P2 (signal labeled ‘‘*’’ in Fig. 1). Howev
and
polymer
P4
>90%
—uncoupled
— molecule
—
— another
•mixtures
b
peaks corresponding to the a- and b-protons
10a200
—
—
P5
>99%
little 1.01
heavier.
1
carrying
side-chain,
H NMR revealed the pr
a
The
coupling
is
thus
estimated
to
25%.
Polystyrene used as standard for GPC calibration curve.
peaks with chemical shifts reminiscent of those
b
Corresponding to ca. 85% imidazolium groups and 15% –OH groups,
a-and b-positions to the OH from P1. Moreover
as a result of partial hydrolysis.
extra peaks was also observed in the 13C NM
O
Br
O
O
OH
P
O
O
OH
OH
* *
log(D)
*
roxyl)acrylate
*
2724 | Polym. Chem., 2012, 3, 2723–2726
NMR vs GPC
This journal is ª The Royal Societ
pseudodesmin-A
• pseudodesmins A is a lipodepsipeptide isolated from
Pseudomonas bacteria collected from the mucus layer in the
skin of the black belly salamander. It show moderate
antibacterial activity against Gram positive bacteria.
with
Bruno Kieffer
José Martins
Davy Sinnaeve
FX Coudert
diffusion in CHCl3
semi-log plot
x-y plot
modeling the oligomerization equilibrium
M + M � M2
M + Mn � Mn+1
M + M2 � M3
[Mn+1 ]
Kn =
[M ][Mn ]
M + M3 � M4
...
• assuming K independent on n
[Mn ] = 2
1−n
�
√
1 + 2Mo K − 1 + 4Mo K
Mo K
�−1+n �
√
1 + 2Mo K − 1 + 4Mo K
1−
2Mo K
�
2
n
# cn
n
2
n
# cn
n
-1/3 (-1 = rod; -1/2 = ran
relating the model and the-1 and
experiment
withequilibrium
cn the concentration
and !Kbetween
Model #1: simple
M + Mn-1 ! Mn, constant
This model has an analytical expression for cn, and has a complicated by analytical expression for
!
D(C):
1
Dn
−α
PolyLog −2 − α,
=
=M
n n-1 ! Mnα, constant
Model #1: Dsimple
equilibrium
M
+
K
√
= Dmax
d
D
F
CK 1 + 4CK 1
�
Using this functional
form to fithas
the experimental
data gives
poor results (graph
vsnC):
This model
an analytical
expression
for
cofn,nD]D
and
has a complicated b
n[M
Dexp = �
D(C):
n[Mn ]
�
�
√
1+2CK− 1+4CK
2CK
450
�
�
√
1+2CK− 1+4CK
2CK
PolyLog −2 − α,
√
D = Dmax
CK 1 + 4CK
400
350
Using this functional form to fit the experimental data gives poor result
300
250
450
200
400
150
0.1
0.2
350
0.5
1.0
2.0
5.0
10.0
20.0
(blue: ! = –1; green: ! = –1/2; black: ! = -1/3)
300
200
modeling the oligomerization equilibrium
150
0.1
0.2
0.5
1.0
2.0
5.0
10.0
20.0
If we try to also fit the value of !, along with Dmax and K, we get:
If we remove the first 5 points, which may
belong to a different regime, we get a much
450
better fit
400
350
300
250
200
150
0.1
0.2
0.5
1.0
2.0
5.0
10.0
20.0
! = –0.85 = –1/1.17, Dmax = 356 "m2/s, K = 0.155 L/mmol
extended model
best fit
in all cases, dF <1.0 ???
extended model
ess
to
ular
elfdegies
gy,
rug
ers,
and
approaches and techniques that allow detailed information
regarding the structure and dynamics of the individual
building blocks and their mutual interactions are therefore
highly desirable.
ide
also
eral
3
er .
,6-9
,
1,12
.
ical
des,
oreM-A.Delsuc, J.C. Martins and B.Kieffer - Chemical Science (2012) DOI: 10.1039/c2sc01088g
ular D. Sinnaeve,
Figure
1. (a) Acetonitrile solution conformation of • CEUM 2012 - Golden Sand
heir
pseudodesmin A, showing only the backbone atoms. (b) Model
•
Poly Proline
• proline
• is the only natural cyclic amino-acid
• induces strong constraints on the
peptidic backbone
• has a strong propensity to adopt PPII
conformation in water
• PPII secondary structure
• is very elongated and thought to be
very rigid
• 3.2 Å per residue; 3 residue per turn
3.2 Å
Measuring dF for poly-proline
R = -0.999607
1 / 1.18
6 different peptides :
P3
P6
P6C
P11C
P14C
P20C
Biophysical Studies of Polyproline Peptides
Measuring dF for poly-proline
Indeed, several biophysical parameters such as diffusion coefficients D
the fractal dimension df can be easily measured. df is a hydrodynamic param
eter evaluating the interaction between a molecule and its environment which
related to the way a 3D element fills up space [12]. It can be calculated fro
D, which can be measured by NMR-DOSY experiments. Theoretically, for a
infinite cylinder df = 1 and for denaturated proteins df = 1.71 [12]. The fract
dimension of a series of polyproline peptides was computed and compared
these theoretical values to have more information on the global shape of the
peptides in solution.
cylinder model
Then, diffusion coefficients of this series of peptides were computed by tw
Ortega and de la Torre. Hydrodynamic properties
different methods and compared to the experimental values. Thanks to Orteg
of rodlike and disklike particles in dilute solution.
and Garcia de la Torre’s equations [13], it is possible to calculate the diffusio
J Chem Phys (2003) 119 (18) pp. 9914-9919
coefficient of a cylinder of diameter d and length l as follows:
D=
kT
1
3l 3
l
l 2
6πη( 16d
2 ) (1.009 + 0.01395 ln( d ) + 0.0788 ln( d ) )
(
On the other hand, Marsh’s equation[14] is adapted to intrinsically diso
dered proteins (IDP) with N residues and P percents of proline in their s
quence:
D=
kT
6πη(2.40(1.24P + 0.904)N 0.509 )
(
molecular
(beads)
modelcorrection” as proline tends to behav
P is called
by the authors
”proline
N Rai,
Nöllmann,and
B adopts
Spotorno,
G Tassara,
O Byron,
differently than
otherM
amino-acids
specific
conformations.
Finally, aMbioinformatics
approach
has been
developed.
A large number
Rocco. SOMO
(SOlution
MOdeler)
differences
conformers of
polyproline
peptides
been generated
in models
silico and studied
between
X-Rayandhave
NMR-derived
bead
design a newsuggest
model ofa PPII
role helices.
for side chain flexibility in protein
hydrodynamics. Structure (2005) 13 (5) pp. 723-34
2. Methods
P3
P6
P6C
P11C
P14C
P20C
2.1. Experimental Fractal Dimension
Diffusion coefficients of seven polyproline peptides (P3 , P6 , P6 C, P11 C, P14 C
P20 C) was measured by a NMR-DOSY experiment on a Bruker Avan
600MHz spectrometer equiped with a cryo-probe
300K.
Solutions
were
• CEUMat2012
- Golden
Sand
• pr
pared with 1mM peptide, 1mM TRIS and 2eq DTT. Pulse sequence was base
Acknowledgments
• IGBMC
• Bruno Kieffer
• Matthieu Tanty
• Justine Vieville
• Christian Koehler
• Lionel Chiron
• Strasbourg - NMRTEC
• Jean-Philippe Stark
• Marie-Aude Coutouly
• Marc Vitorino
• Olivier Assemat
• Redouane Hajjar
• Strasbourg University
• Lionel Allouche
• Bertrand Villeno
• Toulouse University
• M.Malet-Martino
• Y.Prigent
• S.Balayssac
• V.Gilard
• ChimieParisTech - Paris
• F.-Xavier Coudert
• Gent University
• José Martins
• Davy Sinnaeve
• ENS - Lyon
• Cyrille Monnereau
• S. Denis-Quanquin
• Stamford (CT-USA)
• Douglas Harris
• Funding
•
•
•
Agence Nationale de la Recherche
CNRS - INSERM - UdS
NMRTEC

D - Marc-André Delsuc`s

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