Protein Conformation Prediction (Part II)

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Doug Raiford Lesson 18

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Doug Raiford Lesson 18. Protein Conformation Prediction (Part II). 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 - PowerPoint PPT Presentation

Transcript of Protein Conformation Prediction (Part II)

Page 1: Protein Conformation Prediction (Part II)

Doug RaifordLesson 18

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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

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De novo (or ab initio) From the beginning

or from first principles

Comparative/Homology Based Sequence similarity

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Find a similar protein of known structure

Structure should be similar

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Know the phi and psi angles of the similar protein

Can apply those same angles

Known as threading

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What are chances that lengths will the same

Where put longer portionsWhere put gaps

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Once again, MSAs

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3D PSSM (Threading Server)Remember?

Position specific similarity matrix Profiles

3D PSSM performs MSA’s but augments with additional 3D alignments Aligning “known 3D conformations” in three

dimensions

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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

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Secondary structure predictionAccuracy mid to upper 70’sWork the loops to fold secondary

structures into energetically optimal conformation

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See how often aa’s 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)

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Name P(a) P(b) P(turn)Alanine 142 83 66Arginine 98 93 95Aspartic Acid 101 54 146• • •

Valine 106 170 50

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ID regions where 4 out of 6 (3 of 5 for ) contiguous residues have P(a-helix) > 100

Extend the helix in both directions until a set of four contiguous residues that have an average P(a-helix) < 100 is reached.

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1 MAKYNEKKEK KRIAKERIDI LFSLAERVFP YSPELAKRYV ELALLVQQKA HHHHH HHHHHHHHHH H HHHHHHHH HHHHHHHHHH

51 KVKIPRKWKR RYCKKCHAFL VPGINARVRL RQKRMPHIVV KCLECGHIMRT SSTTTT SB TTT B BTTTEEEEE E SSS EEEE EETTTTEEEE

101 YPYIKEIKKR RKEKMEYGGL VPREE

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Chou and Fasman also determined turn frequencies

Most hairpins are three in length When p(-turn) = f(j)f(j+1)f(j+2)f(j+3) is

greater than P() or P()

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Name P(a) P(b) P(turn) f(i) f(i+1) f(i+2) f(i+3)

Alanine 142 83 66 0.06 0.076 0.035 0.058Arginine 98 93 95 0.070 0.106 0.099 0.085Aspartic Acid 101 54 146 0.147 0.110 0.179 0.081• • •

Valine 106 170 50 0.062 0.048 0.028 0.053

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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

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Does this sound familiar?Probability of a sequence of

occurrences?

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Hairpin positio

n 1

Hairpin positio

n 1

Hairpin positio

n 2

Hairpin positio

n 2

Hairpin positio

n 3

Hairpin positio

n 3

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Hidden Markov Model

Hidden states helix, beta sheet, turn

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Proteins organized into Domains

Domains composed of motifs

PFAM Database of

protein families Hidden Markov

Models

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Critical Assessment of techniques for protein Structure Prediction

Biannual conference: contestSecret newly experimentally

determined structures

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CASP1 (1994) | CASP2 (1996) | CASP3 (1998) | CASP4 (2000) | CASP5 (2002) | CASP6 (2004) | CASP7 (2006) | CASP8 (2008) | CASP9 (2010)| CASP10(2012)

CASP1 (1994) | CASP2 (1996) | CASP3 (1998) | CASP4 (2000) | CASP5 (2002) | CASP6 (2004) | CASP7 (2006) | CASP8 (2008) | CASP9 (2010)| CASP10(2012)

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Root mean square (RMS) for angles

No intermol contactsSecondary structureSurfaceBuried

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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

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Build a list of possible conformations (25) for each segment (length 9) Predicted secondary

structure Database of structures

Randomly draw from this list, apply ψ and φ, and score conformation Monte Carlo simulated

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Scoring global conformation hydrophobic burial Electrostatics Disulfide bonding Main chain hydrogen

bonding Strand pairing Sheet formation Helix-strand interactions Excluded volume04/21/23 Protein Conformation Prediction (Part II) 22

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Letter

Name Definition

H Alpha helix (4-12)

Two or more consecutive bridge partners at i and i+4.

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 i+3.

I pi helix Two or more consecutive bridge partners at i and i+5.

T Turn Bridge partner at i+3, i+4, or i+5, 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 i+2.

blank

None Meets none of the criteria above.