Structural Biology:
What does 3D tell us?
Stephen J Everse
University of Vermont
The life of a bio-chemist!!
• Training
– PhD & Postdoc with Russell F. Doolittle, UCSD
• structure of fragment D of fibrinogen
• structures of double-D of fibrin
– Joined the faculty at UVM in 1998
• Structural biologist (crystallographer)
• Current projects
– factor Va
– thioredoxin reductase
– transferrin
Everse Group
Maria Cristina Bravo
Brian Eckenroth, Ph.D.
Fundamental Questions


How do protein cofactors modulate enzymes?
What determines and mediates protein-protein
and protein-membrane interactions?


How is a protein’s function defined by structure?
How does structure prescribe the binding affinity
of a metal?
Coagulation Cascade
Contact
Activation
Pathway
Extrinsic
Pathway
Factor VIIa
Tissue Factor
Membrane
Ca2+
Factor XIa
HMW Kininogen
Membrane
Ca2+ Zn2+
IXa
Factor IXa
Factor VIIIa
Membrane
Ca2+
Prothrombinase
Extrinsic
Tenase
X
IX
Xa
Factor XII
Prekallikrein
HMW Kininogen
“Surface”
Factor Xa
Factor Va
Membrane
Ca2+
II
IIa
“Thrombin”
Intrinsic
Tenase
X
Xa
IX
XI
IXa
Intrinsic
Pathway
XIa
Relative Rate
Prothrombinase of Prothrombin
Activation
Components
“Prothrombinase”
Ca2+FXa
FVa HC
Ca2+
FXa
1
Ca2+FXa
2
Ca2+FXa
20
FVa LC
Ca2+
Prothrombin
-Thrombin
Ca2+FXa
FVaCa
HC2+
FVa LC
W. Gould @2000
300,000
Bovine Factor Vai
A3
Cu2+
A1
Ca2+
C1
Funded by:
NIH
American Society of Hematology
C2
Prothrombinase (Va + Xa)
A2
A1
A3
C2
C1
Hypothetical model
mICA
Eckenroth et al. Protein Science 2010
Outline
• Determining a 3D structure
– X-ray crystallography
• Structural elements
• Modeling a 3D structure
Protein Structures
Primary
Secondary
Tertiary
Quaternary
Arrangement
Alpha helices & of secondary
Packing of several
polypeptide chains.
Beta sheets,
elements in
3D space.
Loops.
Given an amino acid sequence, we are interested in its secondary
structures, and how they are arranged in higher structures.
Amino acid
sequence.
Secondary Structure
 Helix
•
First predicted by Linus Pauling. Modeled on
basis x-ray data which provided accurate
geometries, bond lengths, and angles.
Modeled before Kendrew’s structure;
•
3.6 residues/ turn, 5.4Å/ turn;
•
The main chain forms a central cylinder with
R-groups projecting out;
•
Variable lengths: from 4 to 40+ residues
with the average helix length is 10 residues
(3 turns).
Secondary Structure
The b Sheet
• Unlike  helix, b sheet composed of
secondary structure elements distant in
structure;
• The b strands are located next to each
other
• Hydrogen bonds can form between C=O
groups of one strand and NH groups of an
adjacent strand.
• Two different orientations
– all strands run same direction: “parallel”
– strands in alternating orientation: the
“antiparallel”.
b-Turns
•
Type I: Also referred to as a b turn: Hbond between Acyl O of AA1 and NH of
AA4;
•
Type II, glycine must occupy the AA3
position due to steric effects;
•
Type III is equivalent to 310 helix;
•
Types I & III constitute some 70% of all b
turns;
•
Proline is typically found in the second
position, and most b turns have Asp, Asn, or
Gly at the third position.
Other Secondary Structural
Elements
• Random coil
• Loop
 -turn
– defined for 3 residues i, i+1, i+2 if a hydrogen bond exists
between residues i and i+2 and the phi and psi angles of residue
i+1 fall within 40 degrees of one of the following 2 classes
turn type
classic
inverse
phi(i+1) psi(i+1)
75.0
-64.0
-79.0
69.0
• Disordered structure
Viewing Structures
C or CA
Ball-and-stick
CPK
• It’s often as important to decide what to omit as it is to
decide what to include
• What you omit depends on what you want to emphasize
Ribbon and Topology Diagrams
Representations of Secondary Structures
C
-helix
b-strand
N
Tools for Viewing Structures
• Jmol
– http://jmol.sourceforge.net
• PyMOL
– http://pymol.sourceforge.net
• Swiss PDB viewer
– http://www.expasy.ch/spdbv
• Mage/KiNG
– http://kinemage.biochem.duke.edu/software/mage.php
– http://kinemage.biochem.duke.edu/software/king.php
• Rasmol
– http://www.umass.edu/microbio/rasmol/
RCSB
http://www.rcsb.org/
GRASP
Graphical Representation and Analysis
of Structural Properties
Red = negative surface charge
Blue = positive surface charge
Consurf
• The ConSurf server enables the
identification of functionally
important regions on the
surface of a protein or domain,
of known three-dimensional (3D)
structure, based on the
phylogenetic relations between
its close sequence homologues;
• A multiple sequence alignment
(MSA) is used to build a
phylogenetic tree consistent
with the MSA and calculates
conservation scores with either
an empirical Bayesian or the
Maximum Likelihood method.
http://consurf.tau.ac.il/
How do we show 3-D?
• Stereo pairs
– Rely on the way the brain processes leftand right-eye images
– If we allow our eyes to go slightly walleyed or crossed, the image appears
three-dimensional
• Dynamics: rotation of flat image
• Perspective
Stereo pair: Release factor 2/3
Klaholz et al, Nature (2004) 427:862
Movies
http://pymol.org
Proteopedia
Protein
structures
in the PDB
The last 15 years
have witnessed an
explosion in the
number of known
protein structures.
How do we make
sense of all this
information?
blue bars: yearly total
red bars: cumulative total
Classification of Protein Structures
The explosion of protein structures has led to the development of
hierarchical systems for comparing and classifying them.
Effective protein classification systems allow us to address several
fundamental and important questions:
If two proteins have similar structures, are they related by
common ancestry, or did they converge on a common theme from
two different starting points?
How likely is that two proteins with similar structures have the
same function?
Put another way, if I have experimental knowledge of, or can
somehow predict, a protein’s structure, I can fit into known
classification systems. How much do I then know about that
protein? Do I know what other proteins it is homologous to? Do I
know what its function is?
Definition of Domain
• “A polypeptide or part of a polypeptide
chain that can independently fold into a
stable tertiary structure...”
from Introduction to Protein Structure,
by Branden & Tooze
• “Compact units within the folding
pattern of a single chain that look as if
they should have independent stability.”
from Introduction to Protein
Architecture, by Lesk
• Thus, domains:
• can be built from structural motifs;
• independently folding elements;
• functional units;
• separable by proteases.
Two domains of a
bifunctional enzyme
Proteins Can Be Made From One
or More Domains
•
•
•
•
Proteins often have a modular organization
Single polypeptide chain may be divisible into smaller independent
units of tertiary structure called domains
Domains are the fundamental units of structure classification
Different domains in a protein are also often associated with
different functions carried out by the protein, though some
functions occur at the interface between domains
domain organization of P53 tumor suppressor
1
60
activation
domain
100
300 324 355 363 393
sequence-specific
tetramer- non-specific
DNA binding domain ization
DNA-binding
domain
domain
Rates of Change
• Not all proteins change at
the same rate;
• Why?
• Functional pressures
– Surface residues are
observed to change most
frequently;
– Interior less frequently;
SequenceStructureFunction
Many sequences can give same structure
 Side chain pattern more important than
sequence
When homology is high (>50%), likely to have same
structure and function (Structural Genomics)
 Cores conserved
 Surfaces and loops more variable
*3-D shape more conserved than sequence*
*There are a limited number of structural frameworks*
W. Chazin © 2003
Degree of Evolutionary
Conservation
Less conserved
Information poor
DNA seq
Protein seq
ACAGTTACAC
CGGCTATGTA
CTATACTTTG
HDSFKLPVMS
KFDWEMFKPC
GKFLDSGKLG
S. Lovell © 2002
More conserved
Information rich
Structure
Function
How is a 3D structure determined ?
1. Experimental methods (Best approach):
• X-rays crystallography - stable fold, good quality crystals.
• NMR - stable fold, not suitable for large molecule.
2. In-silico methods (partial solutions based on similarity):
• Sequence or profile alignment - uses similar sequences,
limited use of 3D information.
• Threading - needs 3D structure, combinatorial complexity.
• Ab-initio structure prediction - not always successful.
Experimental Determination
of Atomic Resolution Structures
X-ray
X-rays
Diffraction
Pattern
NMR
RF
Resonance
RF
H0
Direct detection of
atom positions
Crystals
Indirect detection of
H-H distances
In solution
Resolving Power
Signal
•
d
•
Position
Resolving Power:
The ability to see two points that are separated by a given distance as
distinct
Resolution of two points separated by a distance d requires radiation with a
wavelength on the order of d or shorter:
wavelength
Mark Rould © 2007
X-ray Microscopes?
nair
nair
nglass
•Lenses require a difference in refractive index between
the air and lens material in order to 'bend' and redirect
light (or any other form of electromagnetic radiation.)
•The refractive index for x-rays is almost exactly 1.00 for
all materials.
∆ There are no lenses for xrays.
Mark Rould © 2007
Light Scattering and Lenses are
Described by Fourier Transforms
Scattering =
Fourier Transform of
specimen
Lens applies a second
Fourier Transform to
the scattered rays to
give the image
Since X-rays cannot be focused by lenses and refractive
index of X-rays in all materials is very close to 1.0 how do we
get an atomic image?
Mark Rould © 2007
X-ray Diffraction
with
“The Fourier Duck”
The molecule
Images by Kevin Cowtan
http://www.yorvic.york.ac.uk/~cowtan
The diffraction pattern
Animal Magic
The diffraction pattern
Images by Kevin Cowtan
http://www.yorvic.york.ac.uk/~cowtan
The CAT (molecule)
Solution: Measure Scattered Rays, Use
Fourier Transform to Mimic Lens Transforms
Computer
X-Ray Detector
Mark Rould © 2007
A Problem…
A single molecule is a very weak scatterer of X-rays. Most of the X-rays will
pass through the molecule without being diffracted. Those rays which are
diffracted are too weak to be detected.
Solution: Analyzing diffraction from crystals instead of single molecules. A
crystal is made of a three-dimensional repeat of ordered molecules (1014)
whose signals reinforce each other. The resulting diffracted rays are strong
enough to be detected.
A Crystal
•
•
•
3D repeating lattice;
Unit cell is the smallest unit of the lattice;
Come in all shapes and sizes.
Sylvie Doublié © 2000
Crystals come from slowly precipitating the
biological molecule out of solution under conditions
that will not damage or denature it (sometimes).
Putting it all together:
X-ray diffraction
Electron
density map
Rubisco diffraction pattern
Crystallographer
Detector
Computer
Scattered rays
Object
X-rays
Diffraction pattern is a collection of
diffraction spots (reflections)
Sylvie Doublié © 2000
Model
What information does structure
give you?
3-D view of macromolecules at near atomic resolution.
The result of a successful structural project is a “structure”
or model of the macromolecule in the crystal.
You can assign:
- secondary structure elements
- position and conformation of side chains
- position of ligands, inhibitors, metals etc.
A model allows you:
- to understand biochemical and genetic data
(i.e., structural basis of functional changes in mutant
or modified macromolecule).
- generate hypotheses regarding the roles of particular
residues or domains
Sylvie Doublié © 2000
What did I just
say????!!!
• A structure is a
“MODEL”!!
• What does that
mean?
– It is someone’s
interpretation of the
primary data!!!
So what happens when we can’t
get an NMR or X-ray
structure?
2˚ & 3˚ Structure Prediction
Secondary (2o) Structure
Table 10
Phi & Psi angles for Regular Secondary
Structure Conformations
Structure
Antiparallel b-sheet
Parallel b-Sheet
Right-handed -helix
310 helix
p helix
Polyproline I
Polyproline II
Polyglycine II
Phi (F)
-139
-119
-+64
-49
-57
-83
-78
-80
Psi(Y)
+135
+113
+40
-26
-70
+158
+149
+150
Secondary Structure Prediction
• One of the first fields to
emerge in bioinformatics
(~1967)
• Grew from a simple
observation that certain
amino acids or combinations
of amino acids seemed to
prefer to be in certain
secondary structures
• Subject of hundreds of
papers and dozens of
books, many methods…
Simplified C-F Algorithm
• Select a window of 7 residues
• Calculate average P over this window and assign that value to
the central residue
• Repeat the calculation for Pb and Pc
• Slide the window down one residue and repeat until sequence is
complete
• Analyze resulting “plot” and assign secondary structure (H, B, C)
for each residue to highest value
Protein Principles
• Proteins reflect millions of years of evolution.
• Most proteins belong to large evolutionary families.
• 3D structure is better conserved than sequence during
evolution.
• Similarities between sequences or between structures may
reveal information about shared biological functions of a
protein family.
The PhD Algorithm
• Search the SWISS-PROT database and
select high scoring homologues
• Create a sequence “profile” from the
resulting multiple alignment
• Include global sequence info in the profile
• Input the profile into a trained two-layer
neural network to predict the structure
and to “clean-up” the prediction
http://www.predictprotein.org/
Best of the Best
• PredictProtein-PHD (72%)
– http://www.predictprotein.org/
• Jpred (73-75%)
– http://www.compbio.dundee.ac.uk/wwwjpred/index.html
• SAM-T08 (75%)
– http://compbio.soe.ucsc.edu/SAM_T08/T08query.html
• PSIpred (77%)
– http://bioinf.cs.ucl.ac.uk/psipred/psiform.html
Structure Prediction
• Threading
• A protein fold recognition technique that
involves incrementally replacing the
sequence of a known protein structure
with a query sequence of unknown
structure.
• Why threading?
• Secondary structure is more conserved
than primary structure
• Tertiary structure is more conserved
TH
than secondary structure
R
E
A
D
3D Threading Servers
Generate 3D models or coordinates of possible models based on
input sequence
• PredictProtein-PHDacc
– http://www.predictprotein.org
• PredAcc
– http://mobyle.rpbs.univ-paris-diderot.fr/cgibin/portal.py?form=PredAcc
• Loopp (version 2)
– http://cbsuapps.tc.cornell.edu/loopp.aspx
• Phyre
– http://www.sbg.bio.ic.ac.uk/~phyre/
• SwissModel
– http://swissmodel.expasy.org/
• All require email addresses since the process may take hours
to complete
Ab Initio Folding
• Two Central Problems
– Sampling conformational space (10100)
– The energy minimum problem
• The Sampling Problem (Solutions)
– Lattice models, off-lattice models, simplified chain
methods, parallelism
• The Energy Problem (Solutions)
– Threading energies, packing assessment, topology
assessment
Lattice Folding
http://predictioncenter.org/
Critical Assessment of protein Structure Prediction (CASP)
http://folding.stanford.edu/
For the gamers out there…
http://fold.it/portal/
Print & Online Resources
Crystallography Made Crystal Clear, by Gale Rhodes
http://www.usm.maine.edu/~rhodes/CMCC/index.html
http://ruppweb.dyndns.org/Xray/101index.html
Online tutorial with interactive applets and quizzes.
http://www.ysbl.york.ac.uk/~cowtan/fourier/fourier.html
Nice pictures demonstrating Fourier transforms
http://ucxray.berkeley.edu/~jamesh/movies/
Cool movies demonstrating key points about diffraction, resolution,
data quality, and refinement.
http://www-structmed.cimr.cam.ac.uk/course.html
Notes from a macromolecular crystallography course taught in
Cambridge
Evolutionarily Conserved Domains
Often certain structural themes (domains) repeat themselves, but
not always in proteins that have similar biological functions.
This phenomenon of repeating structures is consistent with the
notion that the proteins are genetically related, and that they
arose from one another or from a common ancestor.
In looking at the amino acid sequences, sometimes there are
obvious homologies, and you could predict that the 3-D structures
would be similar. But sometimes virtually identical 3-D structures
have no sequence similarities at all!
The Motif
•
•
•
There are certain favored arrangements of multiple secondary
structure elements that recur again and again in proteins--these
are known as motifs or supersecondary structures
A motif is usually smaller than a domain but can encompass an
entire domain. Sometimes the structures of domains are partly
named after motifs that they contain, e.g. “greek key beta barrel”
It should be noted that the term motif, when used in conjunction
with proteins, sometimes also refers to sequence features with an
associated function, e.g. the “copper binding motif” HXXXXH.
“greek key” motif
beta-alpha-beta motif
Limitations of Chou-Fasman
• Does not take into account long range information
(>3 residues away)
• Does not take into account sequence content or
probable structure class
• Assumes simple additive probability (not true in
nature)
• Does not include related sequences or alignments
in prediction process
• Only about 55% accurate (on good days)
PHD
ZHANG
GOR III
JASEP7
PTIT
LEVIN
LIM
GOR I
CF
Scores (%)
Prediction Performance
75
70
65
60
55
50
45
An Approach
SAS Calculations
• DSSP - Database of Secondary Structures for Proteins
– http://swift.cmbi.ru.nl/gv/start/index.html
• VADAR - Volume Area Dihedral Angle Reporter
– http://redpoll.pharmacy.ualberta.ca/vadar/
• GetArea
– http://curie.utmb.edu/getarea.html
• Naccess - Atomic Solvent Accessible Area Calculations
– http://www.bioinf.msnchester.ac.uk/naccess