Transcript 生物計算

Chapter 7
Protein and RNA Structure
Prediction
暨南大學資訊工程學系
黃光璿
2004/05/24
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Proteins

Built from a repertoire of 20 amino
acids
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7.1 Amino Acids
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胺基酸
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
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中心碳
胺基（NH2）
COOH
氫（H）
側鏈（side chain, R）
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同分異構物
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Fig. 7.2
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pH, pKa, and pI
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pH
-log [H+]
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
pKa


= pH ~ half of the amino acid residues will
dissociate (釋放出H+).
pI
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= pH, isoelectric point for protein
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7.2 Polypeptide Composition
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7.3 Secondary Structure
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7.3.1 Backbone Flexibility
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Conformation of Polypeptide Chain
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Ramachandran Plot
N:藍 C:黑 O:紅 H:白
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二級結構（Secondary Structure）
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Alpha helix
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Beta sheet
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Beta turn
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Loop
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7.3.2 Accuracy of Prediction
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Computational methods
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neural network
discrete-state models
hidden Markov models
nearest neighbor classification
evolutionary computation
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PHD, Predator
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structure prediction algorithms
accuracies in the range 70% ~ 75%
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7.3.3 Chou-Fasman Method
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Identifying Alpha Helices
1.
2.
3.
Find all regions where four out of six
have P(a)>100.
Extend the regions until four with
P(a) < 100 in both directions.
If ΣP(a) > ΣP(b) and the stretch >5,
then it is identified as a helix.
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Identifying Beta Sheets
1.
2.
3.
Find all regions where four out of six
have P(b)>100.
Extend the regions until four with
P(b) < 100 in both directions.
If ΣP(b) > ΣP(a) and the average
value of P(b) over the stretch >100,
then it is identified as a helix.
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Resolving Overlapping Regions
1.
Identified as helix if ΣP(a) > ΣP(b), as
sheet if ΣP(b) > ΣP(a) over the
overlapping regions.
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Identifying Turns
Let P(t) = f(i)xf(i+1)xf(i+2)xf(i+3) for
each position i.
Identify as a turn if
1.
2.
1.
2.
3.
P(t) > 0.000075;
The average of P(turn) over the four
residues > 100;
ΣP(a) < ΣP(turn) > ΣP(b) over the four
residues.
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7.3.4 GOR Method
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on a window of 17 residues
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7.4 Tertiary and Quaternary Structure
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三級結構（Tertiary Structure）

折疊成立體的形狀
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四級結構（Quaternary Structure）

數個三級結構結合成具
有功能的大分子
人類的血球蛋白
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Driving Forces for Folding
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electrostatic forces
hydrogen bonds
van der Waals forces
disulfide bonds
solvent interactions
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7.4.1 Hydrophobicity (疏水性)
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hydrophobic collapse
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
Tend to keep polar, charged residues on the
surface.
The class of membrane-integral proteins is
an exception.
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
sickle-cell anemia (鐮狀細胞性貧血)
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human hemoglobin: 2 alpha & 2 beta
globins
charged glutamic acid residue 
hydrophobic valine residues
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7.4.2 Disulfide Bonds
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7.4.3 Active Structures vs Most Stable
Structures
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Natural selection favors proteins that
are both active and robust.
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Levinthal Paradox
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in 1968
100 residues, each assume 3 different
conformations
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3100 ~ 5x1047 possibilities
Suppose it takes 10-13 s for one trial.
Proteins fold by progressive
stabilization of intermediates rather
than by random search.
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7.5 Algorithms for Modeling Protein
Folding
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Lattice Models
Off-Lattice Models
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7.5.1 Lattice Models
Reduce the search space and make
computing tractable.
 Minimize free energy conformation
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HP-model
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hydrophobic-polar model
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Scoring is based on hydrophobic contacts.
Maximize the H-to-H contacts.
Fig. 7.8
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7.5.2 Off-Lattice Models
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Use RMSD (root mean square deviation)
to measure the accuracy.
Determine Φ and Ψin the allowable
region of the Ramachandran plot.
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7.5.3 Energy Functions and Optimization
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Problems
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The exact forces that drive the folding
process are not well understood.
It is too computationally expensive.
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Summary
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model
representation
scoring function
search (optimization)
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Folding@Home (V. Pande, Stanford)
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7.6 Structure Prediction
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very high accuracy
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< 3.0 Å
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7.6.1 Comparative Modeling
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Also called homology modeling
Rely on the robustness of the folding
code
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1.
2.
3.
4.
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6.
Identify a set of protein structures
related to the target protein.
Align the sequence of the target with
the sequence of the template.
Construct the model.
Model the loop.
Model the side chains.
Evaluate the model.
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7.6.2 Threading
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Given
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a conformation and
a protein sequence,
measure its favorability.
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7.7 Predicting RNA Secondary Structures
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Nearest Neighbor Energy Rules
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Zuker’s Mfold program
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Why study RNA secondary structures?
For understanding of
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gene regulation
expression of protein products
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參考資料及圖片出處
1.
2.
Fundamental Concepts of Bioinformatics
Dan E. Krane and Michael L. Raymer,
Benjamin/Cummings, 2003.
Biochemistry, by J. M. Berg, J. L.
Tymoczko, and L. Stryer, Fith Edition,
2001.
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