Transcript Protein Structure Prediction

Protein Structure Prediction
Why do we want to know
protein structure?
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Classification
Functional Prediction
What is protein structure?
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Primary - chains of amino acids
Secondary - interaction between groups
of amino acids
Tertiary - the organization in three
dimensions of all the atoms in a
polypeptide
Quaternary - the conformation assumed
by a multimeric protein
Primary Structure
Proteins are chains of amino acids joined by peptide bonds
Polypeptide chain
The structure of two amid acids
The N-C-C sequence is repeated throughout the protein, forming the backbone
The bonds on each side of the C atom are free to rotate within spatial constrains,
the angles of these bonds determine the conformation of the protein backbone
The R side chains also play an important structural role
Secondary Structure
Interactions that occur between the C=O and N-H groups on amino acids
Much of the protein core comprises  helices and  sheets, folded into a threedimensional configuration:
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regular patterns of H bonds are formed between neighboring amino acids
the amino acids have similar angles
the formation of these structures neutralizes the polar groups on each amino acid
the secondary structures are tightly packed in a hydrophobic environment
Each R side group has a limited volume to occupy and a limited number of interactions
with other R side groups
 helix
 sheet
Secondary Structure
 helix
 sheet
Secondary Structure
Other Secondary structure elements
(no standardized classification)
- random coil
- loop
- others (e.g. 310 helix, -hairpin, paperclip)
Super-secondary structure
- In addition to secondary structure elements that apply to all proteins
(e.g. helix, sheet) there are some simple structural motifs in some proteins
- These super-secondary structures (e.g. transmembrane domains, coiled
coils, helix-turn-helix, signal peptides) can give important hints about
protein function
Classification
Structural classification of proteins (SCOP)
Class 1: mainly alpha
Class 3: alpha/beta
Class 2: mainly beta
Class 4: few secondary structures
More Classification
Alternative SCOP
Class  : only  helices
Class  : antiparallel  sheets
Class / : mainly  sheets
with intervening  helices
Class + : mainly
segregated  helices with
antiparallel  sheets
Membrane structure:
hydrophobic  helices with
membrane bilayers
Multidomain: contain
more than one class
Protein Structure Review
Q: If we have all the Psi and Phi angles in a protein, do we then have enough
information to describe the 3-D structure?
A: No, because the detailed packing of the amino acid side chains is not
revealed from this information. However, the Psi and Phi angles do
determine the entire secondary structure of a protein
Tertiary structure
Secondary-Structure
Prediction Programs
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* PSI-pred
* JPRED Consensus prediction (includes many of the
methods given below)
* DSC
* PREDATOR
* PHD
* ZPRED
* nnPredict
* BMERC PSA
* SSP
Tertiary Structure
The tertiary structure describes the organization in three
dimensions of all the atoms in the polypeptide
The tertiary structure is determined by a combination of different
types of bonding (covalent bonds, ionic bonds, h-bonding,
hydrophobic interactions, Van der Waal’s forces) between the side
chains
Many of these bonds are very week and easy to break, but hundreds
or thousands working together give the protein structure great
stability
If a protein consists of only one polypeptide chain, this level then
describes the complete structure
Tertiary Structure
Proteins can be divided into two general classes based on their tertiary structure:
- Fibrous proteins have elongated structure with the polypeptide chains arranged
in long strands. This class of proteins serves as major structural component of cells
Examples: silk, keratin, collagen
- Globular proteins have more
compact, often irregular structures.
This class of proteins includes most
enzymes and most proteins involved
in gene expression and regulation
Quaternary Structures
The quaternary structure defines the conformation assumed by a multimeric protein.
The individual polypeptide chains that make up a multimeric protein are often referred to
as protein subunits. Subunits are joined by ionic, H and hydrophobic interactions
Example:
Haemoglobin
(4 subunits)
Structure Displays
Common displays are (among others) cartoon, spacefill, and
backbone
cartoon
spacefill
backbone
Software
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RasMol
Cn3D
Jmol (Chime)
Classic Approach to
Determining Structure?
Determine
biochemical
and cellular
role of protein
Experimentally
determine
3D structure
Infer function,
mechanism of
action
Purify protein
Clone cDNA
encoding
protein
Obtain protein
By expression
Structural Genomics Approach?
genomic
DNA
sequences
predict
proteincoding
genes
Obtain protein
by expression
Obtain protein
In silico
Experimentally
determine
3D structure
Predict
3D structure
homology searches (PSI-BLAST)
Determine
biochemical
and
cellular role
of protein
Sources of Protein Structure
Information?
3-D macromolecular structures stored in databases
The most important database: the Protein Data Bank (PDB)
The PDB is maintained by the Research Collaboratory for Structural Bioinformatics
(RCSB) and can be accessed at three different sites (plus a number of mirror sites
outside the USA):
- http://rcsb.rutgers.edu/pdb (Rutgers University)
- http://www.rcsb.org/pdb/ (San Diego Supercomputer Center)
- http://tcsb.nist.gov/pdb/ (National Institute for Standards and Technology)
It is the very first “bioinformatics” database ever build
Structural Prediction
Computational Modeling
Researches have been working for decades to develop
procedures for predicting protein structure that are not so
time consuming and not hindered by size and solubility
constrains.
As protein sequences are encoded in DNA, in principle, it
should therefore be possible to translate a gene sequence
into an amino acid sequence, and to
predict the three-dimensional structure of the resulting
chain from this amino acid sequence
Computational Modeling
How to predict the protein structure?
Ab initio prediction of protein structure from sequence: not yet.
Problem: the information contained in protein structures lies essentially in the
conformational torsion angles. Even if we only assume that every amino-acid residue
has three such torsion angles, and that each of these three can only assume one
of three "ideal" values (e.g., 60, 180 and -60 degrees), this still leaves us with 27
possible conformations per residue.
For a typical 200-amino acid protein, this
would give 27200 (roughly 1.87 x 10286)
possible conformations!
Q: Can’t we just generate all these
conformations, calculate their energy
and see which conformation has the
lowest energy?
If we were able to evaluate 109 conformations per second, this would still keep us
busy 4 x 10259 times the current age of the universe
There are optimized ab initio prediction algorithms available as well as fold recognition
algorithms that use threading (compares protein folds with know fold structures from
databases), but the results are still very poor
Homology Modeling
Homology (comparative) modeling attempts to predict structure on
the strength of a protein’s sequence similarity to another protein of known
structure
Basic idea: a significant alignment of the query sequence with a
target sequence from PDB is evidence that the query sequence
has a similar 3-D structure (current threshold ~ 40% sequence
identity). Then multiple sequence alignment and pattern analysis
can be used to predict the structure of the protein
Computational modeling: summary
Partial or full sequences
predicted through gene
finding
Similarity search
against proteins
in PDB
Find structures that have a significant
level of structural similarity (but not
necessarily significant sequence similarity)
Alignment can be used to position the
amino acids of the query sequence in
the same approximate 3-D structure
If member of a family with a
predicted structural fold,
multiple alignment can be used
for structural modeling
How do we
do this?
Structural analyses in the lab
(X-ray crystallography, NMR)
Infer structural information (e.g. presence of small
amino acid motifs; spacing and arrangement of
amino acids; certain typical amino acid combinations
associated with certain types of secondary structure)
can provide clues as to the presence of active sites and
regions of secondary structure
3D Comparative Modeling
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Profile Methods - match sequences to folds
by describing each fold in terms of the
environment of each residue in the structure
Threading Methods - match sequences to
structure by considering pairwise interactions
for each residue, rather than averaging them
into an environmental class
HMM Methods - the equivalent state
corresponds to one structurally aligned
position in a structural fold, including gaps
Structural HMM