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Protein Conformation Prediction (Part II)

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Doug Raiford Lesson 18 – PowerPoint PPT presentation

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Title: Protein Conformation Prediction (Part II)


1
Protein Conformation Prediction (Part II)
  • Doug Raiford
  • Lesson 18

2
Review two folding models
  • Framework model
  • Secondary structure first
  • Assemble secondary structure segments
  • Hydrophobic collapse
  • Molten compact but denatured
  • Formation of secondary structure after settles
    in
  • van der Waals forces and hydrogen bonds require
    close proximity

3
Two approaches
  • De novo (or ab initio)
  • From the beginning or from first principles
  • Comparative/Homology Based
  • Sequence similarity

4
Homology based
  • Find a similar protein of known structure
  • Structure should be similar

5
How
  • Know the phi and psi angles of the similar
    protein
  • Can apply those same angles
  • Known as threading

6
Threading issues
  • What are chances that lengths will the same
  • Where put longer portions
  • Where put gaps

Once again, MSAs
7
Popular homology based approach
  • 3D PSSM (Threading Server)
  • Remember?
  • Position specific similarity matrix
  • Profiles
  • 3D PSSM performs MSAs but augments with
    additional 3D alignments
  • Aligning known 3D conformations in three
    dimensions

8
De Novo Approaches
  • Molecular dynamics
  • Summation of all forces exerted at all locations
    simultaneously
  • Computationally intensive
  • Do not fully understand such forces as
    hydro-phobic avoidance of solvent

9
Middle ground
  • Secondary structure prediction
  • Accuracy mid to upper 70s
  • Work the loops to fold secondary structures into
    energetically optimal conformation

10
One approach
  • See how often aas show up at specific positions
    in secondary structure
  • Chou-Fasman
  • Empirical parameters for ?, ?, and ? -turns
  • P(?,aa)f(aa)/ave(?)
  • P(?,aa)f(aa)/ave(?)
  • P(?-turn,aa)f(aa)/ave(?-turn)
  • Name P(a) P(b) P(turn)
  • Alanine 142 83 66
  • Arginine 98 93 95
  • Aspartic Acid 101 54 146
  • Valine 106 170 50

11
Algorithm
  • ID regions where 4 out of 6 (3 of 5 for ?)
    contiguous residues have P(a-helix) gt 100
  • Extend the helix in both directions until a set
    of four contiguous residues that have an average
    P(a-helix) lt 100 is reached.

1 MAKYNEKKEK KRIAKERIDI LFSLAERVFP YSPELAKRYV
ELALLVQQKA HHHHH HHHHHHHHHH H
HHHHHHHH HHHHHHHHHH 51 KVKIPRKWKR RYCKKCHAFL
VPGINARVRL RQKRMPHIVV KCLECGHIMR T SSTTTT SB
TTT B BTTTEEEEE E SSS EEEE EETTTTEEEE 101
YPYIKEIKKR RKEKMEYGGL VPR EE
12
For turns
  • Chou and Fasman also determined turn frequencies
  • Most hairpins are three in length
  • When p(?-turn) f(j)f(j1)f(j2)f(j3) is
    greater than P(?) or P(?)
  • Name P(a) P(b) P(turn) f(i)
    f(i1) f(i2) f(i3)
  • Alanine 142 83 66 0.06
    0.076 0.035 0.058
  • Arginine 98 93 95 0.070
    0.106 0.099 0.085
  • Aspartic Acid 101 54 146 0.147
    0.110 0.179 0.081
  • Valine 106 170 50 0.062
    0.048 0.028 0.053

13
Patterns in usage
  • Patterns can be used to augment these
    statistical approaches
  • In some cases, one side of helices like water
  • Every 4th aa hydrophilic
  • Helps ID helix
  • Helps ID that solvent exposed
  • Other patterns coiled coils

14
Sounds like
  • Does this sound familiar?
  • Probability of a sequence of occurrences?

Hairpin position 1
Hairpin position 2
Hairpin position 3
15
HMMSTR
  • Hidden Markov Model
  • Hidden states helix, beta sheet, turn

16
Motifs
  • Proteins organized into
  • Domains
  • Domains composed of motifs
  • PFAM
  • Database of protein families
  • Hidden Markov Models

17
HMMR and PFAM
18
CASP
  • Critical Assessment of techniques for protein
    Structure Prediction
  • Biannual conference contest
  • Secret newly experimentally determined structures

CASP1 (1994) CASP2 (1996) CASP3 (1998)
CASP4 (2000) CASP5 (2002) CASP6 (2004)
CASP7 (2006) CASP8 (2008) CASP9 (2010)
CASP10(2012)
19
CASP evaluation
  • Root mean square (RMS) for angles
  • No intermol contacts
  • Secondary structure
  • Surface
  • Buried

20
Approaches
  • Have seen comparative homology based
  • HMM based rely on multiple sequence alignments
    homology
  • Now turn to De novo
  • Split into two Ab initio and knowledge based

21
ROSETTA (CASP3 Winner) De Novo Knowledge based
  • Build a list of possible conformations (25) for
    each segment (length 9)
  • Predicted secondary structure
  • Database of structures
  • Randomly draw from this list, apply ? and f, and
    score conformation
  • Monte Carlo simulated annealing procedure

22
ROSETTA (CASP3 Winner)
  • Scoring global conformation
  • hydrophobic burial
  • Electrostatics
  • Disulfide bonding
  • Main chain hydrogen bonding
  • Strand pairing
  • Sheet formation
  • Helix-strand interactions
  • Excluded volume

23
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24
Letter Name Definition
H Alpha helix (4-12) Two or more consecutive bridge partners at i and i4.
B Isolated beta-bridge residue Must not have a neighbor that qualifies it for H, E, G, or I status. Bridge partner is identified in BP1 or BP2 column.
E Strand ("extended") Has at least one bridge partner and at least one neighbor bridged in parallel or antiparallel.
G 3-10 helix Two or more consecutive bridge partners at i and i3.
I pi helix Two or more consecutive bridge partners at i and i5.
T Turn Bridge partner at i3, i4, or i5, but no bridged neighbor that would qualify them for H, G, or I status.
S Bend Local curvature greater than 70 degrees, measured as the angle between alpha carbons at i-2, i, and i2.
blank None Meets none of the criteria above.
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