Protein Crystallography
Mitchell Guss
University of Sydney
Australia

2014 International Year of Crystallography• Declared by the General
Assembly of the United
Nations in June 2013
– Administered jointly by
UNESCO and the IUCr

• See the website for listof activities andresources www.iycr.org

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100+ years of X‐ray crystallography• 1912 Max vonLaue and hiscolleagues
demonstrate thata crystal (copper
sulfate) candiffract X‐rays• Awarded theNobel Prize 1914

Friedrich, Knipping and von Laue, 1912
• Showed that X‐rays behaved as waves• Failed to correctly relate the scattering to theunderlying structure

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100+ years of X‐ray crystallography••

1912 William Lawrence
Bragg interpreted thediffraction from sodium
chlorideAwarded the Nobel Prize
with his father (W.H.
Bragg) in 1915
– W.L. Bragg still remains the
youngest Nobel laureate at
25 years of age

Braggs, 1912
• Showed that the diffraction was equivalent to thereflection from planes drawn through the crystal• Could predict the positions of the diffracted spots
using Bragg’s law: λ = 2dsinθ

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Timeline of biological crystallography ‐ 1
•
•
•
•
•
•
•
•

1895
1912
1912
1929
1951

Röngten: discovers X‐rays (Nobel 1901)
von Laue: demonstrates diffraction (Nobel 1914)
Braggs: first crystal structure (Nobel 1915)
Sumner: crystallises an enzyme (Nobel 1946)
Pauling: protein components α‐helix and β‐sheet(Nobel Chemistry 1954, Peace 1962)
1953 Watson, Crick & Wilkins: DNA structure (Nobel 1962)
1954 Crowfoot‐Hodgkin: vitamin B12, penicillin(Nobel 1964)
1959 Kendrew & Perutz: myoglobin and haemoglobin(Nobel 1962)

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Timeline of biological crystallography ‐ 2
•
•
•
•
•
•

1970+ Klug crystallographic electron microscopy and nucleic
acid‐protein complexes (Nobel 1982)
1985 Michel, Deisenhofer & Huber: the photoreaction
centre, first membrane protein (Nobel 1988)
1997 Boyer & Walker: ATPsynthase a rotating molecule(Nobel 1998)
1998 MacKinnon: K+ ion channel (Nobel 2003)
2000 Yonath, Ramakrishnan & Steitz: the ribosome (Nobel
2009)2011 Lefkowitz & Kobilka: G‐protein coupled receptors(Nobel 2012)

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The Nobel Laureates in Crystallography

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The beginnings of (X‐ray) protein crystallography• 1930’s Dorothy Crowfoot (later Hodgkin) and J.D.
Bernal made the first X‐ray diffraction pictures ofan enzyme – they realised that the crystals had tobe kept wet or they didn’t diffract• 1937 Max Perutz began the structure analysis of
haemoglobin with W.L. Bragg as his supervisor –the structure was not solved until 1961!
What has changed from 1937 to today that enables
the same structure to be solved in minutes?

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Excellent text for biomolecular crystallography• Excellent coverage ofboth the theory andpractice of the subject• Many of my illustrations
come from this text
• See Bernard Rupp’s
website for more detail
http://www.ruppweb.org/default.htm

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What is a crystal?
• An solid containing ofatoms or moleculesthat repeats in three
dimensions• Or, the convolution ofa motif (molecule)with a lattice
Convolution• Place an instance of the motif at eachpoint of the lattice

In this case a “duck” is convoluted
with a 2‐dimensional lattice to give a
2D “duck crystal”

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3‐dimensional protein crystals• The unit lattice is the 3D
set of points described by
the 3 non‐colinear vectorsthat give the repeating
units• The motif is the content
of the unit lattice (Note: it
may be one or a numberof actual molecules)• The unit cell is the unit
lattice with its contents• The crystal is the 3D arrayof unit cells that fill space
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What is diffraction?
••

Diffraction takes place with sound;with electromagnetic radiation, suchas light, X‐rays, and gamma rays; andwith very small moving particles suchas atoms, neutrons, and electrons,
which show wavelike properties.
The phenomenon is the resultof interference (i.e., when waves aresuperposed, they may reinforce orcancel each other out) and is mostpronounced when the wavelength of
the radiation is comparable to thelinear dimensions of the obstacle.
Since X‐rays are of approximately thesame wavelength as inter‐atomic
bonds they will be diffracted bymolecules and crystals.

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Diffraction simulation
http://www.pas.rochester.edu/~ksmcf/p100/java/Optics/Diffraction.html

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Scattering from a molecule

The image is the scattering of the 2D projection
protein molecule on the left. It is the sum of thescattering from each atom (j at position S). The
diffraction (FS) is continuous and can occur in any
direction S.
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Diffraction from a lattice(a, b) Diffraction from a line ofevenly spaced dots (or holes) is aseries of lines perpendicular to therow of dots. The lines have inverse
spacing to the dots.
(c) Diffraction from a 2D array ofdots is an array of dots at rightangles to the original rows.
The array of dots in (c) is the
convolution of the dots in (a) and(b). The diffraction pattern in (c) is
the product of the diffraction
patterns in (a) and (b). What you
see in the (c) is a real lattice and theassociated reciprocal lattice

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The convolution theorem and diffraction from acrystalThe convolution theorem states that undersuitable conditions the Fourier transform of a
convolution of two functions is the pointwise
product of Fourier transforms of the individualfunctions.
Remember a “crystal” is the convolution of alattice and a “molecule”. Therefore thediffraction from a crystal will be the product ofthe diffraction of the lattice and of one
molecule.

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Scattering from a crystal

The underlying pattern remains the same. It is simply “sampled” at points allowed by
the repeating lattice.
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Scattering from a protein crystal

The effect of the crystal is to reinforce the diffraction signal at points where the waves from all
the molecules are in phase. This makes the signal sufficiently large to be measured but all theinformation is theoretically in the scattering from one molecule.

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Scattering from a crystal
The following formula shows how you can calculate the position andmagnitude [F(hkl) is a vector] of the scattered X‐rays if you know the electron‐
density [ρ(x, y, z)] at every position in space.

F(hkl)  V   (x, y, z)exp[2 i(hx  ky  lz)]xyy

Since the electrons are associated with atoms we can express F(hkl) in terms of
the atomic positions and the scattering from a single atom of the appropriate
type.
atoms

F(hkl)   f exp[2 i(hx j  ky j  lz j )]
0
S, j

j1

Where f0 represents the scattering from the jth atom at position (xj,yj,zj). Butthat is the answer – we wish to calculate the electron density [ρ(x, y, z)] fromthe diffraction pattern.
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Calculating the electron density
We can measure the intensities in the diffraction pattern [I(hkl)] that areproportional to the squares of the amplitudes of the structure factors.

I(hkl) ∝ |F(hkl)|2h k l (x, y, z) 1/ V | F(hkl) | exp[2 i(hx  ky  lz   (hkl)]
h k l

The electron
density we aretrying to find

Structure factor
amplitudes we
can measure

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We can’t measure therelative phases – theyneed to be determined –“solving the structure”

20The so‐called ‘phase problem’

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The crystallography experiment

The X‐ray crystallography experiment is like a light microscope except (1) use X‐rays
and not visible light and (2) we have no objective lens for X‐rays so we cannot
refocus to make the image. In other words while we can measure the amplitudesof the diffracted waves we cannot measure their relative phases. This is the“phase problem” of crystallography.
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Overview of protein structure determination

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Life wasn’t meant to be easy!

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Importance of data quality (resolution)

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What has been achieved since 1962

Protein Data Bank (PDB) depositions by year
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PDB depositions by technique

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The experiment
1.
2.
3.
4.
5.
6.
7.
8.

Expression of proteins using molecular biology instead of isolationfrom natural sources – makes more and most importantly purer
protein
Grow crystals – the most uncertain and often the most time
consuming step – use of factorial screens and robotics
Record diffraction data – high speed detectors and intense
synchrotron sources can reduce what once took months tominutes or even seconds
Solve the structure – determine the phases. New methods
including anomalous phasing have significantly improved this step
although it can still be difficult in some cases
Build a model – aided by highly intelligent computer graphics
Refine the structure – optimise the model to fit the data. Fastcomputers have reduced this step from hours to seconds
Deposit the structure in the Protein Data Bank, and;Write a paper – often the slowest step
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Introduction to:

CRYSTALLISATION

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Vapour diffusion – in theory!

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Different apparatus

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Crystallisation plates – for vapour diffusion

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What you are looking for!

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The basic crystallisation diagram

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Successful vapour diffusion experiment

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Screening – can’t do everything

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Can you predict whether a protein will crystallise
The xtalpred server: http://ffas.burnham.org/XtalPred‐cgi/xtal.pl“More efficient to improve the inherent crystallisability than to do further
screening” Rupp, 2010
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Introduction:

DATA COLLECTION (SOURCES)

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Laboratory X‐ray sources

Beamsize at the sample 100 ‐ 200μ depending on optics

In the 1960s and 1970s typicalproblems were considered
insoluble unless crystals at least
300μ could be grown. Even withmodern optics most protein
crystals suitable for a laboratory
source are > 100μ.

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Synchrotron radiation and protein
crystallography• Brilliance– Use of small crystals; rapid data collection• Low Divergence– Resolve close reflections from large unit cells e.g.
viruses• Tunability– Enhance anomalous signal for phasing• Pulsed beam
– Perform time‐resolved experiments on enzymes
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Biologists were not always welcome atsynchrotrons

Synchrotron

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Protein crystallography at the Australian
Synchrotron• Two beamlines
1) Bending magnet, highthroughput, MADphasing, small
molecule
crystallography2) Undulator, highbrilliance, small crystals• Extensive use of
remote access– large country, only one
synchrotron
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Protein crystallography endstations• Robot• CCD detector– Would like Dectris!

• Overhead frame– Easy access– But less stable• On‐line software– Processing on‐the‐flyallows for rapid
evaluation of crystals
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Introduction:

DATA COLLECTION (DETECTORS)Cheiron 2014, Guss

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Detectors ‐ film
• Film– Cheap and linear
response – no longer
used except for teaching– Requires use ofdarkroom– Requires separate
scanner to digitize theimages– Can provide overall viewillustrating the crystal
symmetry
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Precession camera and image

45

Detectors – image plates•

Image plates– Essentially a reuseable
plastic film
• Read out by laser that
detects excited
centres created by X‐
rays• Erased by light– Relatively cheap forlarge area. Widedynamic range. Low
noise.
– Relatively slow
readout (about 120 s).
• Restricts usefulness at
a synchrotron where
an exposure is about
1s.
• Still used at homesources where
exposures are 1‐10
minutes

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Detectors ‐ CCD• CCD– CCD. Need to be tiled forlarge area. Requiringcooling to reduce noise.
Relatively fast readout (<1s). Need to demagnify
the image to match CCD
size.
– Relatively expensive.
Need careful calibration.
– Physically large
Cheiron 2014, GussADSC CCD detector
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Detectors – pixel arrays• Pixel arrays– Can tile many
modules.
– Virtually zero
noise.
– Operates at room
temperature.
– Ultrafast readout
permits
continuous
exposure.
– Very expensive –early adoption of
new technology,
not inherent.

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Introduction:

STRUCTURE SOLUTION AND
REFINEMENT
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Solving the phase problem
•

•

•

•

Marker atom substructure methods do not depend on prior structural knowledge
about the protein (other than the sequence and the structures of the aminoacids). Once the marker atoms (heavy metals, selenium) have been located byPatterson or direct methods starting phases for the modelling can be calculated.
These are de novo or experimental phasing methods.
Density modification are powerful methods for improving the initial phases andare used in practically all de novo phasing experiments. These methods included
solvent flattening, and non‐crystallographic symmetry averaging. As they do not
require any model information they may also be considered experimental
techniques.
Molecular replacement require a similar structure as a molecular search probe.
Replacement is to be understood as the placing of the search model in the crystal
structure not as “substitution”. Phase bias can be a serious problem with thistechnique.
Direct methods exploit the fact that relationships exist between certain sets ofstructure factors. They require very high resolution (1.2 Å or better) for ab initio
determination of a protein structure and have been limited to very small proteins.
They are commonly used for small molecule structures. They are, however, very
important in sub‐structure (marker atom) determination.

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The concept of isomorphous difference
If we add an atom to a protein
crystal and change nothingelse (isomorphous) then the
difference in the diffraction
patterns of the “derivative”
structure with added heavy
atom and the “native” protein
structure approximates thediffraction pattern from theheavy atom alone.

FPA = FP + FA and thus
FA = FP − FA but these are vectors and the amplitudes (things we can measure) don’t add
up: FA ≠ FPA − FP but we can still use the differences to solve the sub‐structure.
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Revision – graphical construction of the structure factor
Graphical illustration of thesummation that yields one
structure factor for a 7‐atomstructure – with 6 relatively
light atoms and one heavier
atom. The resultant structure
factor is Fh.
atoms

Fh   f hj0 .exp(2ihx j )j 1

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The “true” isomorphous differences
When computing the total
structure factor thecontributions from theindividual atoms are
summed vectorially. Thus, if
we add one more atom to aprotein we simply add its
structure factor to that of
the total for the protein.
The radii of the circles are
the amplitudes for theprotein and heavy‐atom
derivative structure factors.

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Graphical illustration of phase determination
Once we know where theheavy atom is we cancalculate FA – the amplitude
AND phase of its contribution.
For each reflection we canmake the construct closing
the vector triangle. We know
the amplitudes FP and FPA
from the experimental
measurements and the total
contribution FA.
If we draw a circle radius, FPA,
at the origin and then movealong FA and draw a circle
radius, FP, there should be
TWO points of intersectionthat satisfy the phase addition
giving two solutions for φP.
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Resolving the phase ambiguity• We have a phase ambiguity if there is: a single isomorphous
derivative (SIR) or anomalous scattering from the native
crystal (e.g. from sulfur) (SAD).
This problem can be resolved:• By adding more derivatives – multiple isomorphous
replacement (MIR)• By using the anomalous signal – single isomorphous
replacement with anomalous scattering (SIRAS) or multiple
isomorphous replacement with anomalous scattering(MIRAS)• By using the dispersive and anomalous signal together –multiple wavelength anomalous diffraction (MAD)• With the help of density modification• With dedicated direct methods programs
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Anomalous scatteringf(S, )  f  f(  )  f
0
(S )

'

"
( )

The scattering from an atom actually contains two wavelength (energy) dependent
terms. These vary rapidly near an absorption edge.
f(S, )  f(S0 )  f(' )  f(" )Cheiron 2014, Guss

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Anomalous scattering for phasing

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Anomalous scattering only significant for heavier elements in a protein• At most synchrotrons PX
beamlines one can accessthe L‐edges for elements
form iodine to uranium
and the K‐edges fortransition metals• Most importantly theedge for selenium is at
0.979 Å (1.27 Kev)
– Se can be introduced into
recombinantly expressed
proteins replacing thesulfur in the amino acidmethionine

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Single Isomorphous Replacement with
Anomalous Scattering (SIRAS)
In this case for eachreflection we have 1
observation of thenative amplitude, FP,
and two for thederivative, FPA‐ and FPA‐.
In the absence of
anomalous scattering(blue circle) there are
two solutions withanomalous scattering(light green circles)
there is only one.

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Early tools for model building

The “Richards” box – named after Fred Richards
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Viewing the structure in a Richards’ box

The reflection of the model in the half‐silvered mirror is seen “superposed”
on the electron‐density contoured on transparent sheets behind the mirror.

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Modern graphics ‐ COOT

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Refinement procedures
•

•

•

•

Local real‐space refinement: fragments of the model once situated in electron‐
density (using COOT or O). The fit (overlap) to electron‐density can be
automatically optimised for short segments of polypeptide. At the same time thepeptide geometry can also be regularised by comparison with a dictionary.
Global reciprocal‐space restrained refinement: the parameters of the model
atoms (x, y, z, and B) and overall parameters such as scale factor, bulk solvent
correction, and anisotropy are refined against the experimental data. The mostcommon target functions are either derived from maximum likelihood or least‐squares.
Cycling in real‐ and in reciprocal‐space: fitting in real‐space (especially manually)
has a large radius of convergence and major errors and omissions in the model canbe corrected. On the other hand reciprocal space refinement makes concerted
movements of all the parameters to improve the overall agreement. Reciprocal
space refinement will improve the electron‐density maps that can then once again
be subject to local real‐space refinement.
Stereochemical restraints: protein crystals rarely diffraction to atomic resolution
so there are insufficient data to refine all the atomic parameters – that is the ratioof observations/variables is too small. This can be addressed either by increasing
the number of observations (adding restraints) or reducing the number of variable
parameters (constraints).

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Monitoring refinement – linear R‐value

| F  F
obs

R h

calc

|

F

obs

h

The R‐value gives an estimate of the overall agreement between theobserved and calculated structure factor amplitudes. It is relatively
insensitive to local errors as the effect is spread over all the data. Hence theimportance of the alternation of real‐ and reciprocal‐space optimisation.
The R‐value generally varies from 0.15 to 0.30 for most protein structuresand is lower for higher resolution structures in general.

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Local minima in a complex landscape

A refinement program may not be able to cross the barrier
necessary to reach the global minimum but it would be obvious
manually.
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How many parameters?
“Numquam ponenda est pluralitas sine necessitate”
William of Ockham (1288‐1347)
Shows in this example how with
sufficient parameters a perfect fit
can be achieved. The result,however, must be physicallymeaningful.
In protein crystallography we would
normally restrict the number ofparameters per atom to 4 or even 3
at low resolution. In small
molecule crystallography weroutinely describe the atomic
motion by 6 parameters making 9
per atom in total.

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Cross‐validation and Rfree
Rfree is simply the R‐value
calculated for a set of reservedreflections that have neverbeen used in the refinement.
The remaining reflections are
termed the working set, Rwork.
Rfree is related to the mean
phase error and is therefore ameasure for phase accuracy
and for model quality.
Rfree is a very useful tool tomonitor the refinement aslong as it decreases along with
Rwork the refinement cancontinue. Beyond that point
too many parameters may
have been added.

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Data‐to‐parameter ratio in protein crystallography
The number ofreflections equals thenumber ofparameters at aresolution of about
2.5 Å. The data only
become sufficient for
unrestrainedrefinement at 1.0 Åresolution.

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Other restraints• Molecules related by non‐crystallographic symmetry can be
restrained to be similar.
– The programs generally allow for different restraints for main‐
chain and side‐chain atoms and weights for tight, medium orloose restraint. These can be useful in the early stages ofrefinement to ensure that subjective model‐building doesn’t
make the structures deviate too much.

• Experimental phase restraints can be applied at early stagesof refinement when the model phases are not very good.
• Displacement parameter (B‐factor) restraints are applied sothat atoms that are bonded to each other in the structure
don’t have wildly different B‐factors, which would bephysically unreasonable.

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SOME EARLY ACHIEVEMENTS IN
MACROMOLECULAR CRYSTALLOGRPAHY

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Vitamin B12
•

•

•
•
•

A complex organic molecule – notable to be synthesised orcharacterised by other means in
the 1950s
Vitamin B12 is a water‐soluble
vitamin with a key role in thenormal functioning of the brain
and nervous system, and for theformation of blood.
Neither fungi, plants, nor animals
are capable of producing vitamin
B12 only bacteria
Humans get their normal intakeof B12 from animal products
It contains an essential cobalt
atom at the centre of a pterin
ring
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Crystal structure of vitamin B12Provided the first complete structural AND
chemical characterisation of vitamin B12

Royal Society stamp honouring Dorothy
Crowfoot Hodgkin

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10 stamps issued to celebrate the 350th anniversary of
the Royal Society (of Great Britain) in 2010

Boyle (Chemistry)
Wallace (Evolution)

Newton (Optics)
Lister (Antisepsis)Franklin (Electricity)
Jenner (Vaccination)
Rutherford (Atomic Structure) Hodgkin (Crystallography)

Babbage (Computing)
Shackleton (Earth Sciences)

Chosen from more than 1400 members including 60 Nobel Laureates – crystallography 1 of 12 sciences, Dorothy Hodgkin the only woman

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The most important discovery in molecular biology:
the birth of the double helix

Sodium deoxyribose nucleate from calf thymus,
Structure B, Photo 51, taken by Rosalind E. Franklin
and R.G. Gosling. This is a diffraction photo from afibre of DNA not a crystal!

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Rosalind Franklin - March 195675

X-ray diffraction and DNA•••

Same experiment that Paulingand Corey used to define the helix & β-sheet protein
structures
Cross pattern indicates a helix
Axial spacings define thedimensions of the helix:Fibre axis
Meridian
0.34 nm,10th line– 0.34 nm (3.4 Å) reflection gives
projected height of repeating unit
– 3.4 nm line spacing gives helix
repeat– 10 lines = 10 repeating units/helix
turn

•
•

Equatorial spacings give radii ofthe helices and their separation
Density and pattern of weak
spots indicate a double helix

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Equator76

X-ray diffraction and DNA
Fibre axis
Meridian
0.34 nm,10th line

Equator0.1 nm = 1 Å = 10-9 m

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Greatest understatement in history?

“It has not escaped our notice that the
specific pairing we have postulated
immediately suggests a possible copying
mechanism for the genetic material”

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Did Rosalind Franklin examine the wrong pattern?
•

2 patterns– A‐form semi‐crystalline– B‐form oriented fibre••

B‐form – highhumidity

A‐form – lowhumidity

Rosalind Franklin worked on the
A‐form because as a
crystallography it seemed to her
to have more information
The extra information gave
greater detail about helix to helix
packing– All the information is in the A‐
form it is just difficult to interpret– Ultimately A‐form data wereused for a full refinement of DNA
by Arnott and Wilkins

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First protein structures: myoglobin & hemoglobin• Crystals were first grown in
1930s• Perutz began work on
hemoglobin in 1938
• Dorothy Hodgkin had
shown that the crystals
needed to be kept wet orthey fell apart• At the time the intensities
of diffraction spots were
estimated ‘by eye’ – took
teams of people months to
get a partial data set
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Structure of myoglobin (Mb)

John Kendrew constructing the first atomicmodel of myoglobin

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Earlier low resolution models of
myoglobin constructed frommodeling clay. α‐helices are seen
as tubes at this resolution.

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Structure of hemoglobin (Hb)

Max Perutz constructing the atomic modelof hemoglobin (> 20 years after starting the
project). Hb is like a complex of 4
myoglobin molecules pointing to an
evolutionary relationship between the two
proteins.

Myoglobin

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Hemoglobin82

Relating structures of hemoglobin (Hb) andmyoglobin (Mb) to their functions•

Hb functions totransport O2 from a
region of high pO2(lungs) to one ofrelatively low pO2(resting muscle)•

Mb binds O2 tightly ata point when Hb isbinding less tightly but
will eventually release
the O2 if the pO2 falls
to a low enough level(working muscle)•

When Hb binds O2 its
structure changes –this change can be
related to the O2binding behaviour

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Use of Hb structure to understand disease• Sickle cellanemia iscaused by asinglemutation (1amino acid in 1
chain of Hb)• The result isthat the Hbmolecules
form fibersthat distort the
red blood cells

Normal & sickled red blood cells

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Hb molecules form a fiber
84

Nobel laureates of 1962
Steinbeck
Wilkins ?
Kendrew

PerutzCheiron 2014, Guss

Crick Watson

85Success:

AN EXAMPLE FROM MYLABORATORY
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Something new about haemoglobin?
Structural basis of haemoglobin capture by
Staphylococcus aureus − stealing haem fromhaemoglobin

Max Perutz and haemoglobin• 1937: Commenced work on
his Ph.D. in Cambridge inthe laboratory of J.D. Bernal(also supervisor of Dorothy
Crowfoot Hodgkin) under
the overall direction of
Lawrence Bragg• 1962: Nobel prize for
Chemistry for the structureof haemoglobin• Now > 600 structures in the
PDB for haemoglobin –what can be new?

Cheiron 2014, GussMax Perutz
with heamoglobin

John Kendrew
with myoglobin

88Bacteria cause majority of emerging infectious disease

Viruses
25.4%

Bacteria
54.3%

10.7%

Protozoa

6.3%
3.3%

Fungi

Helminths

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Jones et al., Nature, 2008

89

Staphylococcus aureus −‘Superbug’
•
•
•
•
•

Pneumonia
Meningitis
Toxic shock syndrome
Bacteremia
Septic endocarditis• Around 25 % of systemic infections in Australia are due tomethicillin‐resistant S. aureus (MRSA)– MRSA strains have until recently been restricted to hospitalsettings but now become evident in the community• There is a pressing need to develop new therapeutics– Need to think outside the box!

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Bacteria require iron
• Iron limitation is one of the most important innate
defences against bacterial infection used bymammals– Low solubility of iron at physiological pH (exists as
Fe3+ in free solution)– Intracellular location of iron
– Sequestration of Fe within iron‐binding proteins• Ferritin, transferin, lactoferin, haemoglobin, myoglobin• In humans, 75% of total Fe is bound tohaemoglobin!

Cheiron 2014, Guss91

Iron acquisition by Staphylococcus aureus• Siderophores bind Fe very
tightly with affinities
ranging over 30 orders tomagnitude (enterochelin
Kd 1052 M‐1)
– Bind free iron or rip ironfrom proteins such astransferrin• Surface receptors, IsdB
and IsdH can bind andextract haem fromhaemoglobin
Hammer & Skaar, Annu. Rev. Micro. 2011, 65:129.
Cheiron 2014, Guss92

Iron acquisition system‐ Isd (Iron regulated surface determinant) system

IsdH
IsdH

N3

IsdA

N1N1

IsdBIsdH

N: NEAT (Near
Transporter) domain

N

N2

IsdHN2Cell wall



Hb

N1
N2



N

IsdD

IsdE N3
IsdH

IsdC

Membrane

IsdG

IsdF
Cytoplasm

IsdI
In IsdH, N1 & N2 bind Hb but not haem; N3 binds haem but not Hb. N1 also binds
haptoglobin but less tightly than Hb (35 vs 10 nM). N2 & N3 of IsdH are homologous
with N1 and N2 of IsdB.
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Questions to be addressed• How does IsdH bind haemoglobin (Hb)?
• How is the haem extracted from Hb and transferred to IsdHN3?
Pre‐existing structural work addressed the issue of haem binding:
1. Structure of IsdA and IsdA‐haem complex (Murphy and colleagues, X‐ray;Clubb and colleagues, NMR)
2. IsdBN2‐haem complex (Murphy and colleagues; IsdBN2 is homologous to
IsdHN3)
3. IsdC‐haem complex (Paoli and colleagues)
4. IsdHN3‐haem complex (Tsumoto and colleagues, X‐ray)
Our structural work:
1. IsdHN1 bound to Hb (Krishna Kumar et al. J. Biol. Chem. 2011)
2. IsdHN1 bound to Hbα (Dickson et al. Acta Cryst. 2014)
3. IsdHN2 & IsdHN2N3 bound to Hb (Dickson et al. J. Biol. Chem. 2014)
Techniques used: X‐ray crystallography, NMR spectroscopy, small angle X‐ray
scattering +Cheiron 2014, Guss

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Cheiron 2014, Guss

95

Structure of HbA(αβ):IsdHN1 complex
IsdHN1Loop 4Loop 8 D

A

C
E

Hb

H

F

B
Resolution

3.0 Å

PDB code

3SZKSpace group

P212121

Rcryst

0.245

Rfree

0.275

Solved by molecularreplacement witheither αHb or βHb assearch modelG

Loop 2Loop 6

G

B

H

E

A

F

 Hb

C

Krishna Kumar et al. J Biol Chem. (2011) 286, 38439-47.

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Key findings from IsdHN1 work
• IsdHN1 binds HbA through its ‐subunit• Sequence differences can explain thepreference for Hb over βHb• K11 of Hb is important for binding– Mutant K11T does not bind IsdHN1• Binding is on opposite side to the haem
pocketCheiron 2014, Guss

97

Haemoglobin receptors‐ IsdH
IsdH
IsdHN1110 residues

IsdHN1N2

IsdHN270 residues
IsdHN3Cheiron 2014, Guss98

SAXS: IsdHN1 & IsdHN2 attached by a flexible
linkerCan model the SAXS data with a flexible modelwith 2 populations – one with a compact form
and the other with an extended form.

Manuscript in preparation
Cheiron 2014, Guss99

Model for HbA capture by IsdHhh
IsdHN1

IsdHN1hLinkerhLinker
IsdHN2
IsdHN2

Linker
IsdHN3Cheiron 2014, Guss

Linker
IsdHN3100

Haemoglobin receptors‐ IsdH
IsdH
IsdHN1110 residues
IsdHN270 residues

IsdHN2N3

IsdHN3Cheiron 2014, Guss101

SAXS: IsdHN2N3 appears to be rigid

IsdHN1N2

IsdHN2N3

Manuscript in preparation
Cheiron 2014, Guss102

IsdHN2N3 linker is structured
PDB code: 2LHR

N

Structured region Val470‐Asp531

C
20 lowest energy structures
Spirig et al., J Biol Chem (2012) 288, 1065-1078.

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Structure of IsdHN2N3 bound to HbA
Crystals:

HbA and IsdN2N3 (Y642A)
purified complex

Diffraction data:synchrotron

MX2 Australian

Structure solution: molecular replacement
Search models:

Stepwise searches with:Hb, IsdHN2 and IsdHN3

Program:

PHASER – 4 IsdHN2N3 boundto HbA tetramer (1 N3domain absent)
N2‐N3 linker was notincluded in search but
clear electron‐density wasseen. NMR model was
fitted to the density.

Refinement:

BUSTER with strong
geometric and NCS
restraints

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Structure of IsdHN2N3 bound to HbA
Linker (2)IsdHN3 (2)IsdHN2 (2)h (2)
IsdHN2 (3)IsdHN3 (1)Linker (1)h (1)

Linker (3)h (3)

4.2 Å resolution
PDB code

3FC4

IsdHN3 (3)IsdHN2 (1)h (4)
h (4)Space group P21212
Rcryst

0.310

Rfree

0.299

IsdHN2 (4)Linker (4)Manuscript in preparation

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Structure of IsdHN2N3 bound to HbA• IsdHN2N3 are bound toboth α and β chains ofHb• Density is seen for thelinks between thedomains but not goodenough to model• The N3 domain of the
4th Isd molecule is not
seen

IsdHN2 (2)IsdHN2 (3)Linker (2)IsdHN3 (2)IsdHN3 (1)Linker (3)h (2)

h (1)

IsdHN3 (3)h (3)

h (4)

IsdHN3 (4) ??

?

Linker (1)Linker (4)IsdHN2 (1)Cheiron 2014, Guss

IsdHN2 (4)106Haem transfer to IsdHN3 from Hb

Difference electron‐density
Anomalous difference density

Cheiron 2014, Guss107

Haem transfer to IsdHN3 from Hb
IsdHN2
IsdHN3
Linkerh
IsdHN3- haem bound
PDB code: 2Z6F
Cheiron 2014, Guss108

Model for IsdH capture of HbA

Cheiron 2014, Guss109

Acknowledgement
Department of Chemistry and Biochemistry,
UCLA, USADavid Gell

Kaavya Krishna Kumar

Robert Clubb
Thomas Spirig
Reza Malmirchegini

Claire DicksonDavid Jacques

Medical School,
Vanderbilt University, USA
Eric P. Skaar
Gleb Pishchany

Joel Mackay

Tom Caradoc-Davies
Australian Synchrotron

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WHAT DOES THE FUTURE HOLD?

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The future with and without crystals• Modeling structures without any experimental data
– By homology with reference to the increasingly large library ofexperimentally determined structures (currently >100,000 in the PDB)
– Ab initio using evermore sophisticated energy algorithms – THIS IS THE
HOLY GRAIL OF THEORETICAL STRUCTURAL BIOLOGY• Free electron lasers providing many orders of magnitude more X‐
rays in very short pulses– Time‐resolved studies of fast reactions– Structures from micro‐crystals– Structures from single particles or – “crystallography without crystals”– THE DREAM OF FELs FOR BIOLOGY• Increasing power of electron microscopy with new direct electron
detectors– Single particle averaging with cryo electron microscopy has yielded
structures to 3.5 Å resolution – MAY SUPPLANT THE NEED FOR FELs
FOR LARGE STRUCTURAL COMPLEXES

Cheiron 2014, Guss112

FEL Facilities
Built/ In construction•

DESY / TTF->FLASH: (2000)–•

Superconducting LINAC, ~1.2 GeV, 1000Å -> 41Å

SLAC / LCLS (2007):–

Room Temperature LINAC, 15 GeV 25Å -> 1.2Å•Trieste / FERMI (2010):•

Spring-8 SACLA (2011)––•

Room Temperature LINAC, 1.2 GeV 1000Å - 100Å (planned)

1.2Å Lasing at
SACLA

Room Temperature LINAC, C-band, 8 GeV 1.2Å -> (0.8Å planned)

DESY / European-XFEL (est 2015)–

Superconducting LINAC, 17.5) GeV, 1Å – 60Å

Proposed / Funded (Parameters and schedule subject to change)•

Pohang XFEL (~2015)––•

PSI Swiss-FEL (~2016)––•

Room Temperature LINAC 14 GeV 50Å- 1Å

LBNL NGLS (2020s)–•

Room temperature LINAC, 6 GeV ~1Å

SLAC LCLS_II (2017)–•

Room Temperature 6 GeV LINAC (C-band)
1Å - 70Å

Shanghai XFEL (?)–•

Room Temperature 10 GeV LINAC
0.6Å to 50Å (planned)

CW superconducting LINAC, 2 GeV, 50Å- 10Å

LANL MaRIE (2020s)–

Room Temperature LINAC, 0.25Å

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Brilliance Comparison

X108

X105

Cheiron 2014, Guss114

Recent experiments ‐ highlights• Gedunken experiment – Hajdu• Mimivirus – Chapman, Hajdu• Photosystem I – Chapman, Fromme, Spence• Cathepsin B ‐ Chapman

Cheiron 2014, Guss115

Hajdu’s thought experiment – Nature, August 2000

(Above) Simulation of the destruction ofa lysozyme molecule with an 2 fs
(FWHM) X‐ray pulse of 3 x 1012 (12 keV)
photons per 100‐nm diameter spot.
(Right) Simulated planar section
through the continuous scattering
image of a single T4 lysozyme molecule.

z

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The real thing – structure of photosystem I
Nature 470, 73‐77, 2011

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117

The real thing – structure of photosystem I

Rate of hits is very low since there is no coordination between the crystal stream and the
X‐ray pulses. The electron density maps at 8.5 Å resolution (left from the 70‐fs data;
right truncated conventional synchrotron data. Refined model is superposed.

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Structure based on single particle diffraction
Nature 470, 78‐81, 2011

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119

Structure based on single particle diffraction• a,b. Experimental
diffraction patterns fromindividual virus particles
in two orientations• c. Transmission electron
micrograph of unstained
mimivirus particle• d,e. Autocorrelation
functions for “a” and “b”• f,g. Reconstructed images
after iterative phaseretrieval
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The first novel structure
Science 339, 227‐230, 2013

Crystals aregrown in vivo
in insect cells

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The first novel structure

Note: These are extremely good statistics forcompared with traditional synchrotron data. The
method results in extremely high values ofredundancy.
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122

The first novel structure
The quality of the structure isevident in the unbiased electron
difference density revealing theunmodelled carbohydrate andbound peptide.

Cheiron 2014, Guss123

Names to remember – Nobel prize?
Janos Hajdu
Laboratory of Molecular Biophysics
Uppsala University, Sweden(Ph.D. Biology, Hungarian Academy of Sciences, 1980)
Will his vision of single molecule diffraction be realised? If so, when?
John H. Spence
Department of Physics
Arizona State University, U.S.A.
(Ph.D. Physics, University of Melbourne, 1973)

Henry Chapman
Centre for Free Electron Science
DESY, Germany(Ph.D. Physics, University of Melbourne, 1992)

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