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NMR Spectroscopy – Part 2. Judith Klein-Seetharaman Department of Structural Biology jks33@pitt.edu. NMR parameters. Chemical Shift. H 2 O. methyl. aromatic. Trp-side-chain NH. OH. aliphatic. Backbone NH. Side-chain H N. H a. Spectrum see handout. 1d 1H NMR spectra.

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nmr spectroscopy part 2

NMR Spectroscopy – Part 2

Judith Klein-SeetharamanDepartment of Structural Biology

jks33@pitt.edu

nmr parameters
NMR parameters

Chemical Shift

H2O

methyl

aromatic

Trp-side-chain NH

OH

aliphatic

Backbone NH

Side-chain HN

Ha

Spectrum see handout

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

1d 1h nmr spectra
1d 1H NMR spectra

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

nmr of membrane proteins
NMR of membrane proteins

In detergent micelle:

In lipid bilayer:

http://www.elmhurst.edu/~chm/vchembook/558micelle.html

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

slide5

Problems!

Detergent peaks

Detergent signals cause dynamic range problems

(Detergent signals cause spectral overlap)

Detergent deuteration is often not feasible

Problem: 1H,1H NOESY spectra do not show protein signals

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

slide6

Selective excitation

B. Selective excitation of the same region as in A. Using excitation sculpting.

A. Selective excitation of the NH region using 90 degree pulse followed by direct observation.

Backbone NH

Tryptophan side chain NH

20

15

10

5

10

5

0

-5

1H Chemical Shift [ppm]

1H Chemical Shift [ppm]

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

2d hsqc
2d HSQC

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

1d projection of hsqc
1d projection of HSQC

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

hsqc spectra
HSQC spectra

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

chemical shift perturbation
Chemical shift perturbation

Figure 2 in “Cap-free structure of eIF4E suggests a basis for conformational regulation by its ligands

Laurent Volpon, Michael J Osborne, Ivan Topisirovic, Nadeem Siddiqui and Katherine LB Borden

The EMBO Journal (2006) 25, 5138–5149

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

assignment is needed
Assignment is needed!

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

several different assignment strategies exist
Several different assignment strategies exist

Most easily automated:

  • HNCO
  • HNCOCACB
  • HNCOCA
  • HNCACB
  • HNCA
  • HNCACO

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

experiments
Experiments

Figure 9. HNCO experiment. The magnetization is transferred (blue arrows) from the HN(i) proton via the N(i) atom to the directly attached CO(i-1) carbon atom and returns the same way to the HN(i) nucleus which is directly detected. The frequencies of all three nuclei (red) are detected. Image and description downloaded from http://www.cryst.bbk.ac.uk/PPS2/projects/schirra/html/3dnmr.htm

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

experiments14
Experiments

Figure 14. HNCA experiment. The HNCA experiment is the prototype of all triple resonance experiments. Starting at an amide proton (H) the magnetization is transferred to the directly attached nitrogen atom (N) which is measured as the first spectral dimension. Then the magnetization is transferred to the Calpha nucleus (CA) which is measured as second dimension. Afterwards, the magnetization is transferred back the same way to the amide proton which is measured as the third (direct) dimension. Image and description downloaded from http://www.cryst.bbk.ac.uk/PPS2/projects/schirra/html/3dnmr.htm

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

experiments15
Experiments

Figure 15. HNCACO experiment. In the HN(CA)CO experiment the magnetization is transferred from the HN(i) proton via the N(i) atom and the CA nucleus (Calpha(i)) to the CO(i) carbon atom and back the same way. The Calpha atom (yellow) acts only as relay nucleus, its frequency is not detected. It is only the frequencies of HN, N and CO (red) which are detected. Image and description downloaded from http://www.cryst.bbk.ac.uk/PPS2/projects/schirra/html/3dnmr.htm

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

assignments
Assignments

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

structure prediction by nmr
Structure Prediction by NMR

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

nmr parameters18
NMR parameters
  • chemical shifts
  • NOE
  • Dipolar coupling
  • Scalar coupling constants (gives dihedral angles)
  • Solvent exchange
  • HetNOE
  • longitudinal relaxation rates (R1)
  • transverse relaxation rates (R2)

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

nmr parameters19
NMR parameters

The Nuclear Overhauser Effect

http://www.oci.unizh.ch/group.pages/zerbe/NMR.pdf

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

hsqc tocsy
HSQC TOCSY

http://www.oci.unizh.ch/group.pages/zerbe/NMR.pdf

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

nmr parameters21
NMR Parameters

Dipolar Couplings

http://www.oci.unizh.ch/group.pages/zerbe/NMR.pdf

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

scalar coupling constants
Scalar coupling constants

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

structure calculations
Structure Calculations
  • Distance geometry
    • Determines ensembles of structures consistent with an incomplete set of distance restraints
      • Metric matrix algorithm
      • Variable target function approach
  • Restrained molecular dynamics
    • Cartesian or torsion-angle coordinate systems
    • Molecular dynamics force fields are supplemented by pseudo energy terms based on the NMR-derived restraints

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

structure prediction from nmr parameters
Structure Prediction From NMR Parameters

Most widely used software suites

  • CNS
    • http://cns.csb.yale.edu/v1.1/
  • XPLOR
    • http://xplor.csb.yale.edu/xplor/

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

nmr parameters25
NMR parameters
  • chemical shifts
  • NOE
  • Dipolar coupling
  • Scalar coupling constants (gives dihedral angles)
  • Solvent exchange
  • HetNOE
  • longitudinal relaxation rates (R1)
  • transverse relaxation rates (R2)

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

comparison of t1 and t2 relaxation
Comparison of T1 and T2 relaxation

http://www.oci.unizh.ch/group.pages/zerbe/NMR.pdf

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture

dynamics in folded unfolded lysozyme
Dynamics in folded/unfolded lysozyme

Unfolded:

Folded:

Smaller rates – more flexible

Computational Biology Laboratory Course – Klein-Seetharaman – NMR Lecture