Transcript Structural Biology: What does 3D tell us? Stephen J Everse University of Vermont.

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
Thioredoxin reductase
DmTR
Eckenroth et al. Biochemistry 2007
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
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.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
http://consurf.tau.ac.il/
Movies
QuickTime™ and a
PNG decompressor
are needed to see this picture.
QuickTime™ and a
Video decompressor
are needed to see this picture.
http://pymol.org
Proteopedia
Higher Level Structures:
Motifs & Domains
Motif is a simple combination of a few secondary
structures, that appear in several different proteins
in nature.
A collection of motifs forms a domain.
Domain is a more complex combination of secondary
structures. It has a very specific function (contains
an active site).
A protein may contain more than one domain.
Super-secondary Structures or Motifs
Domains
"Within a single subunit [polypeptide chain],
contiguous portions of the polypeptide chain
frequently fold into compact, local semiindependent units called domains."
- Richardson, 1981
Domains are:
• can be built from structural motifs;
• independently folding elements;
• functional units;
• separable by proteases.
Typically, globular proteins are organized into one
or more domains.
EGF domain
from p-selectin
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!
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
QuickTi me™ and a
T IFF (Uncompressed) decompressor
are needed to see thi s pi cture.
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
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)
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/
PHD
ZHANG
GOR III
JASEP7
PTIT
LEVIN
LIM
GOR I
CF
Scores (%)
Prediction Performance
75
70
65
60
55
50
45
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
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
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://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