Download Bioinformatics how to predict protein structure using comparative

Bioinformatics how to …
use publicly available free tools to
predict protein structure by
comparative modeling
Proteins are 3D objects with
complex shapes
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Over 60,000 protein structures
have been determined, mostly by
X-ray crystallography (PDB)
3D structure of ~70% of
bacterial and 50% of human
proteins can be predicted
(comparative modeling)
A predicted model simply
illustrates our assumptions
No assumptions, this
is nature telling us
how it is
GNAAAAKKGSEQESVKEFLAKAKEDFLKKWENPA
QNTAHLDQFERIKTLGTGSFGRVMLVKHKETGNH
FAMKILDKQKVVKLKQIEHTLNEKRILQAVNFPF
LVKLEYSFKDNSNLYMVMEYVPGGEMFSHLRRIG
RFSEPHARFYAAQIVLTFEYLHSLDLIYRDLKPE
NLLIDQQGYIQVTDFGFAKRVKGRTWTLCGTPEY
LAPEIILSKGYNKAVDWWALGVLIYEMAAGYPPF
FADQPIQIYEKIVSGKVRFPSHFSSDLKDLLRNL
LQVDLTKRFGNLKDGVNDIKNHKWFATTDWIAIY
QRKVEAPFIPKFKGPGDTSNFDDYEEEEIRVSIN
EKCGKEFSEF
Sequence
Assumption
(protein A is Similar
to protein B)
Result
(protein A is Similar
to protein B)
How do we know that these
proteins are similar?
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Well studied protein
Unknown protein
GLLTTKFVSLLQEAKDGVLDLKL
AADTLAVRQKRRIYDITNVLEGIG
similarity
LIEKKSKNSIQW
prediction

SRRSASHPTYSEMIAAAIRAEKS
RGGSSRQSIQKYIKSHYKVGHN
ADLQIKLSIRRLLAA
How can we make such
assumptions?
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Statistical reliability of the prediction
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E-value - the number of hits one can
"expect" to see just by chance when
searching a database of a particular size
(closer to zero the better)
Z-score – score expressed as a distance
from the mean calculated in standard
deviations (the bigger the better)
Similar, but not homologous
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phosphoribosyltransferase and viral coat protein, identity: 42%, different
folds, different functions
.
.
.
.
.
99 IRLKSYCNDQSTGDIKVIGGDDLSTLTGKNVLIVEDIIDTGKTMQTLLSLVRQY.NPKMVKVASLLVKRTPRSVGY 173
: ||. ||| ||
|.
|| | : |
| | | || | || |:|
| ||.| |
214 VPLKTDANDQ.IGDSLY....SAMTVDDFGVLAVRVVNDHNPTKVT..SKVRIYMKPKHVRV...WCPRPPRAVPY 279
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Different, but homologous
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Histone H5 and transcription factor E2F4, identity 7%, similar fold, similar
function (DNA binding)
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PTYSEMIAAAIRAEKSRGGSSRQSIQKYIKSHYKVGHNADLQIKLSIRRLLAAGVLKQTKGVGASGSFRL
| |
|
|
|
GLLTTKFVSLLQEAKD-GVLDLKLAADTLA------VRQKRRIYDITNVLEGIGLIEKKS----KNSIQW

Steps in comparative
modeling
Recognition
Are there any well characterized
proteins similar to my protein?
Alignment
What is the position-by-position
target/template equivalence
Modeling
Model analysis
What is the detailed 3D
structure of my proteins
Is my model any good?
Recognition
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BLAST, PSI-BLAST or PFAM, FFAS,
metaserver (bioinfo)
Name (PDB code) of the template
Statistical significance of the match (Zscore, e.value, p.value, points)
Alignment
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The same tools as in recognition
(perhaps with different parameters),
editing by hand
Position by position equivalence table
Modeling
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Commercial
programs
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Accelrys (Insight)
Tripos (Sybyl)
…
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Freeware/shareware
/servers
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Modeller (Andrej
Sali)
Jackal (Barry Honig)
SCRWL (Roland
Dunbrack)
SwissModel
Model quality
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Empirical energy based tools
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PSQS (http://www1.jcsg.org/psqs/psqs.cgi)
SwissPDB viewer
Geometric quality
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Procheck, SFCHECK, etc.
(http://www.jcsg.org/scripts/prod/validatio
n/sv3.cgi)
Expectations of comparative
modeling
75
50
25
0
Easy – 100-40% sequence id - strong sequence
similarity, strong structure similarity,
obvious function analogy
Difficult – 40%-25% - twilight zone
sequence similarity, increasing
structure divergence, function
diversification
Fold prediction – below 25% seq id.
no apparent sequence similarity
extreme function divergence
Challenges of comparative
modeling
Modeling
Recognition
Alignment
Trivial
Trivial
Simple
Loop modeling
Trivial
Easy
Simple
Loop modeling
Simple
Challenging
Challenging
Difficult
Very
difficult
Significant
errors
Often
impossible
Significant
errors
Often
impossible
Alignment,
backbone
shifts
Alignment,
backbone
shifts
Recognition
Challenges
100
80
60
40
20
Hands-on Activity

Click below for a hands-on, “bioinformatics how to” activity

Go to
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http://bioinformatics.burnham.org/

Click Structure Biology Course - “Protein
homepage.
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OR Go to….
Modeling Tutorial” Link
in the
http://bioinformatics.burnham.org/SSBC/modeling.html