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

# d

im3

Acq

uir

ed

# d

im

23

Acq

uir

ed

# d

im

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 !