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Classwork II: NJ tree using MEGA.
1. Go to CDD webpage and retrieve alignment of cd00157 in
FASTA format.
2. Import this alignment into MEGA and convert it to MEGA
format http://www.megasoftware.net/mega3/mega.html .
3. Construct NJ tree using different distance measures with
bootstrap.
4. Analyze obtained trees.
2.1 Maximum parsimony: definition of
informative sites.
Maximum parsimony tree – tree, that requires the smallest
number of evolutionary changes to explain the differences
between external nodes.
Site, which favors some trees over the others.
1
2
3
4
5
6
7
A
A
A
A
A
G
G
G
G
C
A
A
A
C
T
G
C
C
T
T
*
T
T
T
T
G
G
C
C
*
Site is informative (for nucleotide sequences) if there are at
least two different kinds of letters at the site, each of which
is represented in at least two of the sequences.
2. Maximum parsimony.
Site 3
1.G
3.A 1.G
G
A
2.C
A
A
4.A 3.A
Tree 1.
2.C
2.C 1.G
A
4.A
A
4.A
Tree 2.
3.A
Tree 3.
Site 3 is not informative, all trees are realized by the same number of
substitutions.
Advantage: deals with characters, don’t need to compute distance matrices.
Disadvantage:
- multiple substitutions are not considered
- branch lengths are difficult to calculate
- slow
2.3 Maximum parsimony method.
1.
Identify all informative sites in the alignment.
2.
Calculate the minimum number of substitutions at each
informative site.
3.
Sum number of changes over all informative sites for each
tree.
4.
Choose tree with the smallest number of changes.
Maximum likelihood methods.
• Similarity with maximum parsimony:
- for each column of the alignment all possible trees are
calculated
- trees with the least number of substitutions are more likely
• Advantage of maximum likelihood over maximum parsimony:
- takes into account different rates of substitution between
different amino acids and/or different sites
- applicable to more diverse sequences
Classwork: maximum marsimony.
1.
2.
3.
Search the NCBI Conserved Domain Database for pfam00127.
Construct maximum parsimony tree using MEGA3.
Analyze this tree and compare it with the phylogenetic tree from
the research paper.
Protein engineering and protein
design.
Protein engineering – altering protein sequence to change protein function or
structure
Protein design – designing de novo protein which satisfies a given requirement
Protein engineering strategies.
Goals:
• Design proteins with certain function
•
Increase activity of enzymes
•
Increase binding affinity and specificity of proteins
•
Increase protein stability
•
Design proteins which bind novel ligands
Protein engineering uses combinatorial
libraries.
•
Random mutagenesis introduces different mutations in many genes of
interest.
•
Active proteins are separated from inactive ones:
- in vivo (measuring effect on the whole cell)
- in vitro (phage display, gene is inserted into phage DNA, expressed,
selected if it binds immobilized target protein)
Specificity of Kunitz inhibitors can be
optimized by protein engineering.
• Kunitz domains – specific inhibitors of
trypsin-like proteinases, highly conserved
structure with only 33% identity.
• Each Kunitz domain recognizes one or
more proteinases through the binding loop
(yellow).
• Phage display method found mutants of
Kunitz inhibitors which have higher
specificity than native ones.
• Modeling of mutant proteins showed that
enhanced specificity is caused by
increased complementarity between
binding loop and the active site.
Native state can be stabilized by reducing
the difference in entropy between folded
and unfolded conformations
G
G  H  TS
U
F
ΔG
Reaction coordinate
Model system: lysozyme from
bacteriophage T4.
• Lysozyme has the ability to lyse certain
bacteria by hydrolyzing the b-linkage
between N-acetylmuramic acid (NAM) and
N-acetylglucosamine (NAG) of the
peptidoglycan layer in the bacterial cell
wall.
• Conformational transition in lysozyme
involves the relative movement of its two
lobes to each other in a cooperative
manner
Disulfide bridges increase protein
stability.
•
Increasing stability by reducing the number of unfolded conformations
(since enthalpic contribution will be the same for folded and unfolded
states).
•
Task: to find positions on backbone where Cysteines can be introduced for
disulfide bonds formation.
Strategy of introducing a new disulfide
bond.
B. Mathews, 1989:
• Analysis of disulfide bonds geometries in existing structures.
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Analysis of all pairs of amino acids which are close in space.
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Energy optimization of candidate disulfide bonds.
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Analysis of destabilizing effect of exchanging native amino acids into Cys.
As a result: three disulfide bonds were introduced through mutagenesis experiments in
lysozyme
Stability of mutants compared to wildtype protein.
Measure of stability – melting
temperature at which 50% of enzyme is
inactivated during reversible heat
denaturation. For wild-type Tm = 42 C.
• all mutants were more stable than
wild-type.
• the longer the loop between Cys, the
larger the effect (the more restricted is
unfolded state).
• the more disulfide bonds were
introduced, the more stable was the
mutant.
From B. Mathews et al
Attempts to fill cavities to stabilize
lysozyme failed…
• Introduction of cavities of size –CH3 group destabilizes protein by ~
1kcal/mol.
• T4 lysozyme has two cavities; mutations Leu  Phe and Ala  Val
destabilize the protein by ~ 0.5-1.0 kcal/mol.
• New side-chains (Val and Phe) adopt unfavorable conformations in
cavities.
Classwork IV: analyzing the lysozyme’s
mutants.
• Retrieve structure neighbors (1PQM and 1KNI) of 2LZM.
• Which mutant might have an increased stability and why?
Can structural scaffolds be reduced in
size with maintaining function?
A. Braisted & J.A. Wells used Z-domain (58 residues) of
bacterial protein A:
• removed third helix (truncated protein - 38 residues);
• mutated residues in the first and second helices;
• used phage display to select active forms;
• restored the binding of truncated protein.
Designing an amino acid sequence that
will fold into a given structure.
• Inverse protein folding problem:
designing a sequence which will fold
into a given structure – much easier
than folding problem!
• B. Dahiyat & S. Mayo: designed a
sequence of zinc finger domain that
does not require stabilization by Zn.
• Wild type protein domain is
stabilized by Zn (bound to two Cys
and two His); mutant is stabilized by
hydrophobic interactions.
Paracelsus challenge: convert one fold into
another by changing 50% of residues.
•
Challenge because all proteins with > 30%
identity seem to have the same fold.
•
L.Regan et al: Protein G (mainly beta-sheet)
was converted to Rop protein (alpha-helical)
by changing only 50% residues