Supplementary Material for
Utilization of paramagnetic relaxation enhancements for high-resolution
NMR structure determination of a soluble loop-rich protein with sparse
NOE distance restraints
Kyoko Furuita, Saori Kataoka, Toshihiko Sugiki, Yoshikazu Hattori, Naohiro
Kobayashi, Takahisa Ikegami, Kazuhiro Shiozaki, Toshimichi Fujiwara and
Chojiro Kojima
This file includes:
page
Supplementary Materials and Methods
2-6
Supplementary Discussions
7-8
Supplementary References
9-10
Supplementary Tables S1 to S4
11-16
Supplementary Figures S1 to S12
17-33
1
Supplementary Materials and Methods
Preparation of Sin1CRIM protein
Construction of the pCold-GST expression vector encoding Sin1CRIM,
SpSin1 (amino acid 247-400), expression and purification of unlabeled,
13C,15N-labeled
15N-
and
Sin1CRIM protein were performed as previously described
(Kataoka et al. 2014). Briefly, the cDNA encoding Sin1CRIM was amplified by PCR
and genetically inserted into pCold-GST vector (Hayashi and Kojima 2008).
Recombinant Sin1CRIM was overexpressed in E. coli RosettaTM (DE3) (Novagen).
Cells overexpressing Sin1CRIM were harvested by centrifugation and then
physically disrupted by ultrasonication. The crude membrane debris was
pelleted by ultracentrifugation and supernatants were then loaded onto a
Glutathione Sepharose 4B column (GE Healthcare). Sin1CRIM was eluted using a
buffer containing 50 mM reduced glutathione. The N-terminal GST tag of the
Sin1CRIM protein was removed by digestion using Human rhinovirus (HRV) 3C
protease. Following protease treatment, Sin1CRIM protein sample was further
purified by size-exclusion column chromatography (SEC).
PRE-derived distance restraints
PRE-derived distance restraints were calculated as follows. First, the
contribution of oxidized spin label to relaxation rates was calculated from
intensity ratios of 1H-15N HSQC spectra in the paramagnetic and diamagnetic
states (Figures S2 and S3), according equation (1) (Battiste and Wagner 2000).
Iox/Ired = R2exp(-R2spt)/R2+R2sp
(1)
2
where Iox and Ired are the peak intensities in the paramagnetic and diamagnetic
states, respectively, and t is the total INEPT evolution time of the 1H-15N HSQC
(10 ms). R2 and R2sp are the transverse relaxation rate for amide spin in the
diamagnetic states, and the contribution of electron spin in the paramagnetic
states to the relaxation rate, respectively. R2sp was then converted into distances
using the following equation,
r = [K/ R2sp(4τc + 3τc/ 1+ωh2τc2)]1/6
where r is the distance between the electron center on MTSL and nuclear spins,
c is the correlation time for the electron-nuclear interaction, h is the Larmor
frequency of the proton nuclear spin, and K is 1.23 10-32 cm6s-2 composed of
physical constants (Battiste and Wagner 2000). For calculating the distances,
the approximation was made that c was equal to the global correlation time of
the protein estimated from the molecular weight of the protein (10 ns), and R2
was estimated from the line width at half-height (1/2) in proton dimension of
1H-15N
HSQC spectra using the equation, R2 = 1/2, under reduced conditions
(76.8 ms on average). Line width and peak intensities were estimated using the
program Sparky.
All peak intensity ratios were calculated from the peak height ratios. The
error range of the peak intensity ratio was much larger than the expected from
the noise level. In an effort to evaluate the error range experimentally, the peak
intensity ratios showing more than 1 were focused on. Because the peak
intensity ratio is between 0 and 1, the peak intensity ratios showing more than 1
could be the indicators of the experimental error. The averaged value and the
3
error range of the peak intensity ratios showing more than 1 were 1.06 ± 0.15
(2.5σ). In other words, 20% errors were expected at a maximum. Therefore the
intensity ratios showing less than 0.8 were subject to the influence of PRE.
PRE-derived distance restraints were introduced between amide protons
and Cβ atoms of mutated residues with the error of ± 7 Å. The smaller error of ± 6
Å gave the larger target function values of CYANA, and the larger error of ± 8 Å
did not show significant improvements. Thus, the error of ± 7 Å is reasonable in
our system, although this error was much larger than the previously reported
values, 2 - 4 Å (see Table S4 and references therein). This large error could be
from the flexibility of MTSL. If this flexibility is a key factor, ensemble
representations of spin-labels with two time-point measurements (Iwahara et al.
2004, 2007) will be useful. At least, further studies are necessary to understand
why the error is so large in our system.
Structure calculation for structure determination
Structure calculations were performed combined with automated NOE
assignments. The structure calculations were performed in the absence or
presence of PRE-derived distance restraints obtained from 9 spin-labeled
mutants (T280C, S282C, R291C, S301C, K312C, L332C, S371C, T384C and
A394C). The input data for each structure calculation is provided in Table 1.
The 10 structures with the lowest target function that were calculated by
CYANA were further refined using Xplor-NIH 2.31 (Schwieters et al. 2003, 2006).
The initial structures for Xplor-NIH structure refinements were generated with a
single MTSL nitroxide label at each mutated position. In Xplor-NIH structure
4
calculations, PRE distance restraints were introduced for distances between
NS1 atoms of MTSL labels and amide protons with an error of 4Å. The structure
refinements were performed with NOE distance, PRE distance and dihedral
angle restraints. 10 structures were calculated starting from each structure. The
10 lowest energy structures were selected and analyzed. The atomic
coordinates of the refined structures of Sin1CRIM and the structural restraints
including PREs and RDCs have been deposited in the Protein Data Bank with
accession code 2RUJ.
Structure calculations using the fixed list of NOE upper distance limits
Calculations were performed in the absence or presence of PRE-derived
distance restraints obtained from the 9 spin-labeled mutants referred to in the
previous section. Except for the PRE-derived distance restraints, NOE upper
distance and dihedral angle restraints created by CYANA in the structure
calculations combined with automated NOE assignments in the presence of
PRE-derived distance restraints, which are described in the previous section,
experimentally determined ,  and χ1 dihedral angles are used as structural
constraints.
Structure calculations with varied number of PRE restraints
PRE-derived distance restraints comprising 12.5, 25, 37.5, 50, 62.5, 75,
or 87.5% of the original PRE-derived distance restraints, derived from the 9
spin-labeled mutants, were prepared by randomly selecting restraints from the
original restraints using Microsoft Excel. Ten PRE-derived distance restraints
5
were prepared with respect to each percentage group. Each group of
PRE-derived distance restraints was introduced in structure calculations
combined with automated NOE assignments. Except for PRE-derived distance
restraints, the input data was the same as those used in the structure
calculations for the structure determination described above.
Structure calculations using modified NOE peak lists
First, at the lowest threshold, manual peak picking was applied to
and
15N-edited
noise level for
13C-
NOESY spectra. The threshold was set to 4- and 6-times the
13C-
and
15N-edited
NOESY-HSQC spectra, respectively. Then a
series of NOE peak lists were prepared by increasing the threshold of the
NOESY spectra from 100% to 120%, 140%, 160%, 180% and 200%. These
peak lists were then used in structure calculations combined with automated
NOE assignments. Except for the peak lists, the input data was the same as
those used in the structure calculations for the structure determination described
above.
6
Supplementary Discussions
Impact of the quality of NOESY spectra on structure determination
The impact of the quality of NOESY spectra on structure determination
was investigated by modifying the NOE peak lists. First, at the lowest thresholds,
manual peak picking was applied to
13C-
and
15N-edited
NOESY spectra. The
structure was calculated by the automated NOE assignment procedure using
PRE-derived distance restraints and a series of NOE peak lists (Figure S12).
These NOE peak lists were prepared by increasing the threshold of the NOESY
spectra from 100% to 200%. That is, by increasing the threshold of the NOESY
spectra, the number of NOE peaks decreases. All structures except for that
shown in Figure S12 were calculated using the NOE peak lists prepared at
140% threshold.
When the threshold of the NOESY spectra was higher than 140% of the
original, the backbone RMSD increased significantly (Figure S12). When the
threshold of the NOESY spectra was lower than 140% of the original, no
significant change in backbone RMSD was observed (Figure S12). These
results indicate that a certain level of quality of the NOESY spectra is required
for convergence of the calculated structure, even if PRE-derived distance
restraints are used. Furthermore, it is conceivable that some weak NOEs are
critical for convergence. On the other hand, the RDC correlation coefficients did
not show a clear dependence on the threshold of the NOESY spectra (Figure
S12). These results indicate that the accuracy of the structure tends to be
7
maintained independently of the quality of the NOESY spectra, if PRE-derived
distance restraints are used.
Technical implementation of PRE data in structure calculation
Battiste and Wagner utilized distances derived from paramagnetic
broadening of 1H-15N HSQC spectra in protein structure determinations, where
flexibility of spin label was considered by taking wide distance error range
(Battiste and Wagner 2000). Another way to consider flexibility of spin label was
proposed by Iwahara et al., where flexibility of spin label is considered by
representing it as an ensemble of spin labels (Iwahara et al. 2004). By using this
approach, 1H-PRE data arising from a flexible paramagnetic group could be
accurately utilized in structure refinement (Iwahara et al. 2004). In order to
accurately measure PRE relaxation rates, a two time-point measurement has
been proposed (Iwahara et al. 2007). In this study, we used a method proposed
by Battiste and Wagner. This method is used for 19 out of 20 NMR structures of
membrane proteins found in the database 'Membrane Proteins of Known
Structure Determined by NMR' (http://www.drorlist.com/nmr/MPNMR.html)
(Table S4).
8
Supplementary References
Battiste JL & Wagner G (2000) Utilization of site-directed spin labeling and
high-resolution heteronuclear nuclear magnetic resonance for global fold
determination of large proteins with limited nuclear overhauser effect data.
Biochemistry 39: 5355-65.
Bhattacharya A, Tejero R & Montelione GT (2007) Evaluating protein structures
determined by structural genomics consortia. Proteins 66: 778–95.
Bowie JU, Lüthy R & Eisenberg D (1991) A method to identify protein sequences
that fold into a known three-dimensional structure. Science 253: 164–70.
Hayashi K & Kojima C (2008) pCold-GST vector: a novel cold-shock vector
containing GST tag for soluble protein production. Protein Expr Purif 62:
120-127.
Kataoka S, Furuita K, Hattori Y, Kobayashi N, Ikegami T, Shiozaki K, Fujiwara T
& Kojima C (2014) 1H,
15N
and
13C
resonance assignments of the conserved
region in the middle domain of S. pombe Sin1 protein. Biomol NMR Assign, in
press.
Iwahara J, Schwieters CD & Clore GM (2004) Ensemble approach for NMR
structure refinement against (1)H paramagnetic relaxation enhancement data
arising from a flexible paramagnetic group attached to a macromolecule. J. Am.
Chem. Soc. 126: 5879–96.
Iwahara J, Tang C & Clore GM (2007) Practical aspects of 1 H transverse
9
paramagnetic relaxation enhancement measurements on macromolecules. J.
Magn. Reson. 184: 185–195.
Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R & Thornton JM (1996)
AQUA and PROCHECK-NMR: programs for checking the quality of protein
structures solved by NMR. J. Biomol. NMR 8: 477–86.
Lüthy R, Bowie JU & Eisenberg D (1992) Assessment of protein models with
three-dimensional profiles. Nature 356: 83–5.
Sippl MJ (1993) Recognition of errors in three-dimensional structures of proteins.
Proteins 17: 355–62.
10
Table S1. Mutants of Sin1CRIM designed for the site-directed spin labeling.
Mutant
constructiona expressionb solubilityb
purification
NMR
measurement
S248C
×
-
-
-
-
S256C
×
-
-
-
-
D260C
×
-
-
-
-
S269C





T280C





S282C





S287C
×
-
-
-
-
R291C





S298C
×
-
-
-
S301C





K304C
×
-
-
-
-
K312C

Δ



S317Cc





S319C
×
-
-
-
-
G321Cc





Q331C

Δ
Δ


L332C





V333C
×
-
-
-
-
Q341C





R349C
×
-
-
-
-
G355Cc





E359C
×
-
-
-
-
D360C
×
-
-
-
-
F361Cc





A363C
×
-
-
-
-
R366C





S371C





K382C
×
-
-
-
-
11
T384C





A386Cc





Q392C
×
-
-
-
-
A393C

NAd
-
-
-
A394C





Y395C
×
-
-
-
-
S399C





aThe
generation of plasmid containing the appropriate mutation was either
successful () or unsuccessful (×).
bThe
expression level and solubility of the mutants was either high () or low (Δ).
cMutants
dNot
designed after the structure determination.
attempted.
12
Table S2. Backbone RMSDs and RDC correlation coefficients of structures
determined in the presence of PRE-derived distance restraints derived from a
single spin-labeled sample or 9 spin-labeled samples.
labeled residue backbone RMSD RDC correlation coefficient
280
2.32 ± 0.29
0.64 ± 0.10
282
2.35 ± 0.73
0.60 ± 0.10
291
2.80 ± 0.58
0.73 ± 0.11
301
3.70 ± 0.77
0.49 ± 0.15
312
2.40 ± 0.51
0.62 ± 0.06
332
1.96 ± 0.85
0.38 ± 0.20
371
3.60 ± 0.98
0.64 ± 0.07
384
3.19 ± 0.84
0.49 ± 0.11
394
2.67 ± 0.77
0.58 ± 0.05
9 residuesa
0.91  0.17
0.86  0.05
aResidues
280, 282, 291, 301, 312, 332, 371, 384 and 394.
13
Table S3. Structural statistics for refined structures of Sin1CRIM.
Completeness of resonance assignment (%)
Backbone
93
Side chain
71
Aromatic
20
Conformationally restricting restraints
Distance restraints
NOE
Total
929
Short range (|i-j|1)
612
Medium range (1<|i-j|<5)
126
Long range (|i-j|5)
191
PRE
Total
867
Upper distance restraints
163
Lower distance restraints
704
Hydrogen-bond restraints
0
Disulfide restraints
0
Dihedral angle restraints
Total
212
Backbone
200
Side chain
12
Distance violation
> 0.5 Å
0
Dihedral angle violation
0
>10
Model quality
Rmsd backbone atoms (Å)1
1.0
Rmsd heavy atoms (Å)1
1.5
Rmsd bond lengths (Å)
0.011
Rmsd bond angles ()
1.4
RDC correlation coefficient
0.89 ± 0.03
14
PROCHECK Ramachandran statistics1,2,3
Most favored regions (%)
84.2
Additionally allowed regions (%)
12.6
Generously allowed regions (%)
2.4
Disallowed regions (%)
0.7
Global quality scores (raw/Z score)3
Verify3D4
0.20/-4.17
Prosall5
0.26/-1.61
PROCHECK (-)1,2
-0.54/-1.81
PROCHECK (all)1,2
-0.41/-2.42
MolProbity clash score6
30.57/-3.72
1calculated
for amino acids 275-395
2Laskowski
et al. 1996
3calculated
using PSVS version 1.5 (Bhattacharya et al. 2007)
4Sippl
1993
5Bowie
6Davis
et al. 1991; Lüthy et al. 1992
et al. 2007
15
Table S4. Membrane proteins determined using PRE restraints found in the
database, “Membrane Proteins of Known Structure Determined by NMR”.
Protein
PDB ID
Method1
Reference
Mistic
1YGM
A (TROSY)
Roosild et al. 2005
FXYD1
2JO1
A (HSQC)
Teriete et al. 2007
KCNE1
2K21
A (TROSY)
Kang et al. 2008
DsbB
2K73
A (TROSY)
Zhou et al. 2008
DsbB
2K74
A (TROSY)
Zhou et al. 2008
DAGK
2KDC
A (TROSY)
Van Horn et al. 2009
Rv1761c
2K3M
A (HSQC)
Page et al. 2009
ArcB
2KSD
A (TROSY)
Maslennikov et al. 2010
QseC
2KSE
A (TROSY)
Maslennikov et al. 2010
KdpD
2KSF
A (TROSY)
Maslennikov et al. 2010
UCP2
2LCK
A (TROSY-
Berardi et al. 2011
HNCO)
Proteorhodopsin
2L6X
Combination of Reckel et al. 2011
A and B
HIGD1A
2LOM
A (TROSY)
Klammt et al. 2012
HIGD1B
2LON
A (TROSY)
Klammt et al. 2012
TMEM14A
2LOP
A (TROSY)
Klammt et al. 2012
FAM14B
2LOQ
A (TROSY)
Klammt et al. 2012
TMEM141
2LOR
A (TROSY)
Klammt et al. 2012
TMEM14C
2LOS
A (TROSY)
Klammt et al. 2012
Human glycine
2M6I
A (HSQC)
Mowrey et al. 2013
2M8R
A (TROSY)
Liang et al. 2013
receptor alpha1 TM
t-SNARE
Syntaxin-1A
1Method
that were used to implement PRE in structure determination. A, Method
proposed by Battiste and Wagner. Experiments that were used to measure PRE
are in parentheses; B, Method proposed by Iwahara et al.
16
Figure S1. Concentration dependence of the peak intensities of the 1H-15N
HSQC spectra of MTSL-conjugated Sin1CRIM (K312C). The peak height ratios
between 200 and 50 μM, and 100 and 50 μM are shown in gray and black points,
respectively. The averaged values are 0.90 ± 0.04 and 1.03 ± 0.03 for 200μM /
50 μM (glay) and 100 μM / 50 μM (black), respectively. These values indicate the
peak intensity at 200 μM is 10% lower than the expected.
17
(Figure S2, continues on the next page)
18
(Figure S2, continues on the next page)
19
Figure S2. Overlay of
1H-15N
HSQC spectra of Sin1CRIM WT (blue), and
MTSL-conjugated mutant in the diamagnetic (green) and paramagnetic (red)
states. G321C, Q341C and G355C mutants showed dramatic chemical shift
changes. In the case of Q331C, the 1H-15N HSQC spectrum could not be
measured with sufficient signal-to-noise ratios. The 1H-15N HSQC spectrum of
R366C was completely altered with a change from the oxidized to reduced state.
20
(Figure S3, continues on the next page)
21
Figure S3. Intensity ratio of 1H-15N HSQC peaks of the paramagnetic and
diamagnetic states. Error bars indicate experimental uncertainties based on the
noise level in the NMR spectra.
22
Figure S4. Time dependence of the average peak heights of 1H-15N HSQC
spectra of MTSL-conjugated Sin1CRIM (K312C). The spectra are serially
measured 15 times.
23
Figure S5. Concentration dependence of the PRE values of MTSL- conjugated
Sin1CRIM (K312C). PRE ratios between 100 and 50 μM of protein are shown. The
PRE values are evaluated from the intensity ratio of 1H-15N HSQC spectra in the
presence or absence of 1 mM ascorbic acid. The errors are calculated from the
root-mean-square of the spectral noises. The averaged value is 1.03 ± 0.05,
indicating the PRE values are same at difference protein concentrations, 100
and 50 μM.
24
(Figure S6, continues on the next page)
25
(Figure S6, continues on the next page)
26
Figure S6. Location of PRE-derived distance restraints obtained for each mutant.
MTSL-conjugated cysteine residues are shown by yellow spheres. Red,
residues restrained by upper distances; magenta, residues restrained by both
upper and lower distances; cyan, residues restrained by lower distances.
27
Figure S7. The correlation plots of back-calculated versus experimental RDCs
for the lowest energy structure calculated by CYANA in the absence of PRE (a),
the lowest energy structure calculated by CYANA in the presence of PRE (b) and
the lowest energy structure refined by Xplor-NIH (c). The correlation coefficients
are 0.63 (a), 0.92 (b) and 0.87 (c). The slope of the line through the origin is 1.
28
Figure S8. (a) A superimposed representation of 10 lowest energy structures.
(b) A ribbon representation of the lowest energy structure.
29
Figure S9. NOEs used for the structure calculations are shown by thin black
lines on the lowest target function structure of Sin1CRIM.
30
Figure S10. RMSD values of backbone atoms and correlation coefficients
between experimental RDC values and back-calculated RDC values obtained
from one of the final 10 structures with the lowest target function, which were
calculated using reduced PRE distance restraints (left) and PRE distance
restraints obtained with any one of S77C, F121C or A146C in addition to 100%
of the PRE distance restraints (right).
31
Figure S11. NOE-derived long-range distance restraints that increased by
employing PRE-derived distance restraints in the automated NOE assignments
by CYANA. NOEs are shown by lines on the lowest target function structure of
Sin1CRIM.
32
Figure S12. Influence of the quality of NOESY spectra on structure calculations.
Valuable NOE peak lists, which were prepared by increasing the threshold of the
NOESY spectra from 100% to 200%, were used in structure calculations. The
RMSD values of backbone atoms and correlation coefficients between
experimental and back-calculated RDC values using the calculated structures.
33