Protein structure determination

and our software tools Mark Berjanskii

Edmonton Februrary 2015

Outline

1) X-ray crystallography

2) Cryo-electron microscopy (Cryo-EM)

3) NMR spectroscopy

4) Mass spectrometry

5) MS23D

Why do we need to know protein

structure?

Why do we need to know protein

structures?

1) Prediction of protein function from 3D structure (e.g. fold,

motifs, active site prediction)

2) Mechanism of protein function (e.g. enzyme catalysis,

structural effect of known mutations).

3) Rational drug design

4) Design of novel proteins with novel function. Sequence-to-

function and sequence-to-structure predictions

1) Ubiquitin

- degradation by the proteasome,

2) Ubiquitin-like modifiers

- function regulation by post-translation

modification

X-ray crystallography

X-ray crystallography

Quality metrics: 1) Experimental data: -Number of reflections -Signal to noise ratio 2) Model-to-experiment agreement: - R factor -R free factor

3) Coordinate uncertainty: - B-factor 4) Stereo-chemical normality: - backbone torsion angles (Ramachandran plot) - bond length, angles - side-chain torsion angles

X-ray Resolution

Minimum spacing (d) of crystal lattice planes that still provide measurable diffraction of X-rays. Minimum distance between structural features that can be distinguished in the electron-density maps.

High resolution Low resolution High resolution

Low resolution

200,000 reflections

500 reflections Many reflections Few reflections

Resolution and protein quality

X-ray resolution by proxy

ResProx would be able to detect

most of the withdrawn X-RAY

structures from the Murthy lab

ResProx vs X-ray resoltion

Number of protein structures

per year

Cryo-electron microscopy

(Cryo-EM)

Cryo-electron microscopy

Image formation in the electron

microscope.

(a) Electrons, emitted by a source that is

housed under a high

vacuum, are accelerated down the

microscope column . After passing through

the specimen, scattered electrons are

focused by the electromagnetic lenses of

the microscope

(b) Schematic illustrating the principle of

data collection for electron tomography. As

the specimen is tilted relative to the

electron beam, a series of images is

taken of the same field of view.

(c) Rendering of selected projection views

generated during cryo-electron tomography

3D image from Cryo-EM

Examples of Cryo-EM images

(a,b) Illustration of spiral architecture of

the nucleoid in Bdellovibrio

bacteriovorus showing

(a) a 210 Å thick tomographic slice

through the 3D volume of a cell

(b) a 3D surface rendering of the same

cell, with the spiral nucleoid

highlighted

(c) Higher magnification view of a

tomographic slice through the cell,

showing well-separated nucleoid

spirals and ribosomes (dark dots)

distributed at the edge of the

nucleoid.

(d) Expanded views of 210 Å thick

tomographic slices, showing top-

views of polar chemoreceptor arrays.

Cryo-EM revolution in structural

biology

Cryo-EM can now achieve a resolution

necessary for de novo structure

determination

Cryo-EM structures <5Å

Examples of “high-resolution”

de novo structures from Cryo-EM

A) transient receptor

potential cation

channel subfamily V

member 1 (TRPV1) ion

channel

B) F420-reducing [NiFe]

hydrogenase

C) large subunit of the

yeast mitochondrial

ribosome

D) γ-secretase.

NMR spectroscopy

Protein NMR spectroscopy Experiment Spectra processing Spectra assignment

NOE assignment

Distance restraints

Model generation

Resolution of NMR structures

Macromolecular NMR spectroscopy for the non-spectroscopist. Kwan AH, Mobli M, Gooley PR, King GF, Mackay JP. FEBS J. 2011 Mar;278(5):687-703

Protein NMR structures from

Wishart group 2B0F

Human Rhinovirus

3C Protease

1DE1

Oxidized bacteriophage

T4 glutaredoxin.

1DE2

Reduced bacteriophage

T4 glutaredoxin.

1NHO

Thioredoxin-like protein

(Mt0807)

1Z9V

MTH0776

Secondary structure from NMR chemical

shifts PANAV

s

CSI

Torsion angles from NMR

chemical shifts

Accessible surface area from

NMR chemical shifts

Prediction of NMR chemical

shifts from structure

Protein model building from NMR data

Validation of NMR protein models

Mass-spectrometry

Distance restraints from MS cross-

linking experiments

Distance restraints

Model generation

Residue accessibility by MS

limited proteolysis

Secondary structure localization

by MS HD exchange

Problem Many structural solutions may be compatible

with few restraints and solvent exposure info

1 restraint

2 restraints

3 restraints

Trypsin-inhibitor complex (1TAB)

Lys222E-Lys16I, Lys224E-Lys16I, and

Lys60E-Lys31I (21Å links)

Probing native protein structures by chemical cross-

linking, mass spectrometry and bioinformatics. Leitner A,

Walzthoeni T, Kahraman A, Herzog F, Rinner O, Beck M,

Aebersold R. Mol Cell Proteomics. 2010 Mar 31.

How many distance restraints

do we need?

For 2,3,4:

Young, M. M., Tang, N., Hempel, J. C., Oshiro, C. M., Taylor, E. W., Kuntz, I. D., Gibson, B.

W., and Dollinger, G. (2000) High throughput protein fold identification by using

experimental constraints derived from intramolecular cross-links and mass

spectrometry. Proc. Natl. Acad. Sci. U. S. A. 97, 5802-5806

1) Atomic resolution - 10- 20 restraints per residue (NMR)

2) Residue resolution – 3 restraint per residue

3) Fold – 1/10 restraint per residue ( = protein length/10 )

4) Complex of rigid bodies – 3 restraint per complex

5) Experimentally biased comparative / ab initio model – 1 restraint

Distance restraint requirements for different levels of

structure determination

One contact per 12 residues is

enough to model protein topology

MS-based structure determination

requires knowledge-based information

Cross-

links

Residue exposure

Advanced

Force-field:

solvation term

full electrostatic

knowledge-based

potentials

Fragment

information

Homology

information

Disulfide restraints can bias conformational

search for BPTI towards the native state No restraints Three disulfide restraints

Native No restraints

RMSD= 8.2A

3 disulfide restraints

RMSD= 2.14A

BPTI from disulfide distance restraints

PrP 90–232 modeled using the interlysine

cross-link distance constraints.

Mol Cell Proteomics. 2012 Jul;11(7): Use of proteinase K nonspecific digestion for selective and

comprehensive identification of interpeptide cross-links: application to prion proteins.

Petrotchenko EV1, Serpa JJ, Hardie DB, Berjanskii M, Suriyamongkol BP, Wishart DS, Borchers CH.

N-terminus of PrP 68-228 has propensity to interact with the end of helix B, which is the first PrP region to unfold at low pH

HB

HC HA

HC HA HB

HA

HC

pH 5.2 pH 3.2

CA of N-terminal residue Gly68 is shown with blue spheres.

MS-GAMDy

Rigid-body docking in Cartesian space by XPLOR

Monomer A Monomer B

Monomer B backbone optimization

Monomer A backbone optimization

Docking

Dimer backbone optimization

Distances for monomer A

Starting model for monomer A

Distances for monomer B

Starting model for monomer B

Inter distances for dimer

XPLOR rigid-body docking with initial alignment by distance restraints

1 min, 64 structures with no restraint violations from 64

Beta-strand pairing - 5 beta-strands Unknowns: 1) parallel or anti-parallel 2) interacting residues 3) internal or external

Shift Partial coverage

assign ( ( resid 1 OR resid 2 OR resid 3 OR resid 4 OR resid 7 OR resid 6 OR resid 5 ) and name N ) ( ( resid 12 OR resid 13 OR resid 14 OR resid 17 OR resid 16 OR resid 15 ) and name O ) 2.8 0.8 0.2 assign ( ( resid 1 OR resid 2 OR resid 3 OR resid 4 OR resid 7 OR resid 6 OR resid 5 ) and name O ) ( ( resid 12 OR resid 13 OR resid 14 OR resid 17 OR resid 16 OR resid 15 ) and name N ) 2.8 0.8 0.2 assign ( ( resid 1 OR resid 2 OR resid 3 OR resid 4 OR resid 7 OR resid 6 OR resid 5 ) and name N ) ( ( resid 66 OR resid 67 OR resid 68 OR resid 71 OR resid 70 OR resid 69 ) and name O ) 2.8 0.8 0.2 assign ( ( resid 1 OR resid 2 OR resid 3 OR resid 4 OR resid 7 OR resid 6 OR resid 5 ) and name O ) ( ( resid 66 OR resid 67 OR resid 68 OR resid 71 OR resid 70 OR resid 69 ) and name N ) 2.8 0.8 0.2 assign ( ( resid 41 OR resid 42 OR resid 43 OR resid 45 OR resid 44 ) and name N ) ( ( resid 66 OR resid 67 OR resid 68 OR resid 71 OR resid 70 OR resid 69 ) and name O ) 2.8 0.8 0.2 assign ( ( resid 41 OR resid 42 OR resid 43 OR resid 45 OR resid 44 ) and name O ) ( ( resid 66 OR resid 67 OR resid 68 OR resid 71 OR resid 70 OR resid 69 ) and name N ) 2.8 0.8 0.2 assign ( ( resid 41 OR resid 42 OR resid 43 OR resid 45 OR resid 44 ) and name N ) ( ( resid 48 OR resid 49 ) and name O ) 2.8 0.8 0.2 assign ( ( resid 41 OR resid 42 OR resid 43 OR resid 45 OR resid 44 ) and name O ) ( ( resid 48 OR resid 49 ) and name N ) 2.8 0.8 0.2

24 possible arrangements of beta-strands into a beta-sheets via XPLOR ambiguous restraints Example:

RMSD = 0.6A Convergence ~ 20%

Fragment-based modelling

MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQR MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQR MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQR MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQR MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQR MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQR

Torsion angle restraints

Distance restraints

CS23D SFAssembler

Homodeller

Starting model pool

Ubiquitin from 2FAZA 4.86A

Template-derived distance restraints

82 N-O restraints

1UBQ GAMDy model0.6A

Ubiquitin from 2FAZA 4.86A

82 N-O restraints

GAMDy model 4.8A

GAMDy model 2A