hifi nmr : part1 automated backbone assignments using 3d->2d marco tonelli national magnetic...
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HIFI NMR : part1
automated backbone assignments using 3D->2D
Marco Tonelli
National Magnetic Resonance Facility At Madison NMRFAM
Recording multidimensional experiments is time costly
In conventional multidimensional experiments, all the individual frequency domains are incremented (sampled) independently
t
1 FID30 sec.1D
t2
t1
t1: 128 FIDs64 min.
2D
t1
t2
t3
t1x t2: 128x128=16,384 FIDs5 days 16 hrs.
3D
t1x t2 x t3 : 32x32x32=32,768 FIDs11days 9 hrs.
4D
Increasing number of indirect dimensions in conventional multidimensional:
• collection time increases exponentially
• need to reduce number of increments to keep collection time reasonable: low resolution
• not very practical above 3 dimensions
• impossible above 4 dimensions
Fast methods
Hadamard spectroscopy
single-scan NMR
so-fast NMR
Reduced Dimensionality
Reduced Sampling
Reduced Dimensionality Techniques
two or more indirect dimensions are evolved simultaneously
mix/prep mixingt2
t3preparation t1
t2
t3
t1
Conventional 3D spectrum
t1 and t2 are incremented independently
t3
t1/t2
t1 and t2 are incremented simultaneously point by point
RD spectrum
1 2
12
3
1 2
3
1 2
12
12
3
t3
costx sint
sintx sint
RD spectrumt1/t2
FT
1 = x,y 2 = y
Reduced Dimensionality Techniques …
1 2
1 2
12
3
t3
cost x cost
sint x cost
RD spectrumt1/t2
FT
1 = x,y 2 = x
t3
t1
cost
sint
2D spectrum
FT
11
3
1 = x,y
mix/prep mixingt2
t3preparation t1
1 2
The peaks in RD experiments can either be separated into different spectra (GFT - Szyperski) or into different regions of the same spectrum (TPPI - Gronenborn)
TPPI Method
1+ 2
1- 2
3
TPPI offset
2D
1
1 12
GFT
1+ 2
1- 2
3
- 2
+ 2
Reduced Dimensionality Techniques …
2D RD planes of 3D spectra 2D projections of 3D spectra tilted planes
1H13C
15N
tilted plane1H-13C/15N plane
of CBCA(CO)NH
45°
1H
13C/15N
1H13C
15N90° plane1H-15N plane
of CBCA(CO)NH
90°
1H
15N
1H13C
15N0° plane1H-13C plane
of CBCA(CO)NH
0°
1H
13C
2D planes of 3D CBCA(CO)NH
Reduced Dimensionality Techniques …
20° 45° 70°
By changing the ratio between the two simultaneously evolving dimensions we can change the projection angle of the tilted plane t 15N
t 13C
1H13C
15N
Projection Reconstruction
In principle, it is feasible to reconstruct a 3D spectrum from a number of 2D tilted planes collected at different angles.
Reduced Dimensionality Techniques …
Simple 3D objects can be reconstructed from 2D projections collected at different angles
3D objectreconstructed
object
3D
reconstruction
1H13C
15N
3D reconstrucion
High-resolution Iterative Frequency IdentificationHIFI
multiple tilted planes are used
simultaneously evolving indirect frequencies are extracted from two-dimensional RD spectra
angle of tilted planes is chosen adaptively in real time
GFT / TPPI method Projection-Reconstruction
n-dimensional experiments are run as two-dimensional RD spectra
split peaks can be separated into different spectra (GFT) or different regions of the same spectrum (TPPI)
indirect frequencies are extracted from analysis of split patterns
multiple tilted planes are collected at different angles
n-dimensional spectra are reconstructed from several tilted planes
Reduced Dimensionality Techniques …
GFT / TPPI method Projection-Reconstruction
reconstructing spectra can be very complicated or impossible with overlapped peaks and/or low S/N
it relies on combining multiple indirect dimension to resolve overlapped peaks
analysis can be very complicated
difficult to automate
difficult to automate
with each added indirect dimension:• S/N is reduced by √2• collection time is doubled
multidimensional frequency information can only be extracted after spectra reconstruction
HIFI
by changing the tilt angle, HIFI has greater potential of resolving overlapped peaks than GFT/TPPI methods
since only frequency information is extracted from tilted planes, HIFI does not need to resolve the problem of reconstructing nD volumes
easier to analyze
easier to automate
by adaptively choosing the next tilt angle, HIFI optimizes information gain while minimizing time collection
Reduced Dimensionality Techniques …
orthogonal planes
HIFI flowchart
peak list
NO
hifi.sh
generate_peaklist.sh
this process can be automated in vnmr
predict next besttilted angle
does tilted plane add new information
???
tilted plane
YES
mORTHO0 macro
HIFI algorithm for predicting best tilted angle
find a tilt angle that maximizes a dispersion function
f(p)
does tilted plane add new information
???
YES
collect tilted plane
X° NOpeak list
dispersion function, f (p), measures the dispersion of the putative peaks on the selected
tilted plane
Eghbalnia et al JACS 127 (36), 12528 -12536, 2005
orthogonal planes
0° 90°
predicted chemical shift distribution
assign a probability of a peak being in a given voxel, p
add 45° tilted plane
add additional tilted planes
Combined peaks from HIFI planes are in magenta
Hand picked peaks from 3D spectrum in green
HIFI on CBCA(CO)NH
putative peaks from C-H/N-H planes
Using HIFI for backbone assignments
HNCOHN(CO)CAHNCACBCA(CO)NHHN(CA)CBHNCACB
Modified BioPack experiments for backbone assignments
NH sensitivity enhanced
TROSY option
standard sequences are robust and offer the best S/N for backbone assignments
we rely on HIFI ability to adaptively select tilted planes to resolve overlapped peaks
added HIFI option for collecting tilted planes13C and 15N indirect dimensions are evolved simultaneously
added semi-constant time 15N evolution to allow collecting tilted planes with more indirect points for higher resolution
optimized for cryogenic probes
Needs AUTOMATION !!!
run HIFI macro - tilted planes
run tilt angle predicting program
read predicted tilt angle
experiment #1 in list
outline of vnmr macro for automated HIFI data collection
process tilted plane
save tilted plane
run experiment to collect tilted plane at suggested angle
tilt>0
tilt=0
run program to extract 3D frequencies
all experiments
in list completed??
3D peak list
YES
run probabilistic backbone assignmentsNO
ne
xt
ex
pe
rim
en
t in
li
st
number of residues = XX
HNCOHN(CO)CAHNCACBCA(CO)NHHNCACBHN(CA)CB
hnco_tilt_0hncoca_tilt_0hnca_tilt_0cbcaconh_tilt_0hncacb_tilt_0hncb_tilt_0
hnco_hsqchnco_hsqchnco_hsqchnco_hsqchnco_hsqchnco_hsqc
input list of experiments
preparation - orthogonal planes
• run othogonal planes for all experiments
• process orthogonal planesoptimize processing parameters
• save orthogonal planes
all experiments list:collect 0º plane adjust 13C s.w.
1H-15N HSQC :use as 90º planeadjust 15N s.w.
HNCO
HN(CO)CA
HNCA
CBCA(CO)NH
HN(CA)CB
HNCACB
0º
90º
47º62º
2
0º
90º52º
69º
2
0º
90º51º
71º
29º38º
4
0º
90º49º
63º
44º
32º
4
0º
90º
42º59º
31º28º
4
0º
90º
39º45º
31º18º15º5
0º
90º
41º38º34º
3
0º
90º
15º
69º
44º
3
0º
90º56º
67º
22º40º
4
0º
90º48º
57º
40º
31º
4
0º
90º53º
62º
41º
11º4
0º
90º
40º45º
37º26º8º
57º
6
brazzein - 53 a.a.ubiquitin
76 a.a.flavodoxin
176 a.a.
71º
0º
90º
42º51º
20º
63º
4
0º
90º
26º
70º
34º
53º
4
0º
90º
46º59º
18º
39º34º
52º
7
0º
90º
46º60º
18º
35º26º
53º70º
7
0º
90º
24º35º
18º 14º11º
33º
3º
39º
29º
9
0º
90º53º
70º
28º
41º
14º
60º
35º
7
0º
90º
43º64º
2
0º
90º45º
77º
2
0º
90º41º
63º
27º33º
4
0º
90º65º
77º
54º
42º
4
0º
90º
31º42º
24º12º5º5
~9hrs~12hrs ~14hrs ~48hrs
wild-type RI mutant
HIFI backbone assignments - recap
we have developed HIFI for extracting 3D peaks using 2D tilted planes
by adaptively predicting the best tilt angles, we guarantee that all available 3D data is extracted using the minimum number of tilted planes
we have adapted the most robust 3D experiments for backbone assignments
to be recorded using HIFI-NMR
we have successfully automated HIFI backbone data collection for proteins of small/medium size
automated HIFI is robust and allows to extract 3D peaks lists with:
• least amount of spectrometer time
• minimum human intervention
protein sample conv
entio
nal N
MR
exp
erim
ents
size
peak overlap
T2 relaxation
deuteration
selective labeling
TR
OS
Y
HIFI
long
er ti
me
≡ hi
gher
S/N
reso
lve
over
lap
4
com
plic
ated
3
long
er ti
me
≡ hi
gher
S/N
Combine information from different experiments
Improving algorithm for peak detection
Improving algorithm for tilt angle prediction
where is HIFI going …
reso
lve
over
lap
com
plic
ated
low
er S
/N
654
To
tal
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NMR data
collection
chemical shift
assignments
structure
calculation
The BIG picture
HIFI NMR : part2
conclusions and other applications
Marco Tonelli
National Magnetic Resonance Facility At Madison NMRFAM
BACKBONE ASSIGNMENTS
HIFI: application to chemical shift assignments
HIFI adaptiverobust : collect all the information needed
efficient : collect only the minimum amount information needed to answer the question
TODAY:
HNCO
HN(CO)CA
HNCA
CBCA(CO)NH
HNCACB
HN(CA)CB
peak listcollect
tilted planepredict best
angleorthogonal
plane
HIFI
collect tilted plane
predict bestangle
orthogonalplane
HIFI
BACKBONE ASSIGNMENTS
HIFI: application to chemical shift assignments
HIFI adaptiverobust : collect all the information needed
efficient : collect only the minimum amount information needed to answer the question
TOMORROW:
HNCO
HN(CO)CA
HNCA
CBCA(CO)NH
HNCACB
HN(CA)CB
collect tilted plane
predict bestangle
orthogonalplanepeak list
HIFI
peak listcollect
tilted planepredict best
angleorthogonal
plane
HIFI: application to chemical shift assignments
HIFI adaptiverobust : collect all the information needed
efficient : collect the only the minimum amount information needed to answer the question
THE DAY AFTER TOMORROW:
HIFI
select experimentpredict best tilt
pool ofexperiments
collect tilted plane
collect preliminary data
BACKBONEASSIGNMENTS
HIFI: other applications
any application that makes use of information extracted from a 3D experiment can be speeded up by recording a tilted plane instead
HIFI can then be used to ensure that maximum information is recovered by predicting the best angle to use for recording the tilted plane
t2
t3
t1
Conventional 3D spectrum
t3
t1/t2
tilted plane
HIFI: other applications
1H13C
15N
1H
13C + 15N
1H
13C - 15N
two tilted planes are obtained for each experiment run: “plus” and “minus”
• different peak distribution – bigger potential of resolving overlapped peaks
• different noise distribution – can provide measure of confidence of data obtained by analyzing spectra
HIFI: extraction of RDC
extraction of RDCC’N using a modified HNCO pulse sequence (Bax)
record two 3D C’-N-H experiments:1. reference spectrum2. attenuated spectrum - intensity of peaks is
modulated by coupling: JC’N + DC’N
1H13C
15N
1H13C
15N
reference attenuated
Example:
Conventional method:
extract JC’N + DC’N coupling from the ratio between intensity of corresponding peaks in the reference and attenuated spectra
repeat for isotropic and aligned samples
HIFI: extraction of RDC
record two tilted C’-N-H planes at the optimal tilt angle:1. reference spectrum2. attenuated spectrum - intensity of peaks is
modulated by coupling: JC’N + DC’N
HIFI method:
extract JC’N + DC’N coupling from the ratio between intensity of corresponding peaks in the reference and attenuated spectra
repeat for isotropic and aligned samples
13C + 15N
1H
reference
1H
attenuated
1H
13C - 15N
1H
reference attenuated
analyze “plus” and “minus” planes independently compare the results from the two plenes to get
measure of data confidence combine the results from the two planes
Who did the work ?
John MarkleyMilo Westler
Fariba Assadi-PorterShanteri Shingh
Rob TylerAnna FuzeryNick Reiter
Claudia Cornilescu
sample preparation
tilt prediction and peak extraction
algorithms
Arash BarhamiHamid Eghbalnia
pulse sequencesvnmr automationRDC extraction
Marco TonelliKlaas Hallenga
Gabriel Cornilescu
NMRFAM
800MHz 900MHz750MHz
600MHz
Thank you !