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Protein Structural Prediction Protein Structure is Hierarchical Structure Determines Function The Protein Folding Problem What determines structure? Energy Kinematics How can we determine structure? Experimental methods Computational predictions Primary Structure: Sequence

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structure determines function
Structure Determines Function

The Protein Folding Problem

  • What determines structure?
  • Energy
  • Kinematics
  • How can we determine structure?
  • Experimental methods
  • Computational predictions
primary structure sequence
Primary Structure: Sequence
  • The primary structure of a protein is the amino acid sequence
primary structure sequence5
Primary Structure: Sequence
  • Twenty different amino acids have distinct shapes and properties
primary structure sequence6
Primary Structure: Sequence

A useful mnemonic for the hydrophobic amino acids is "FAMILY VW"

secondary structure loops
Secondary Structure: , , & loops
  •  helices and  sheets are stabilized by hydrogen bonds between backbone oxygen and hydrogen atoms
second and a half ary structure motifs
Second-and-a-half-ary Structure: Motifs

beta helix

beta barrel

beta trefoil

quaternary structure multimeric proteins or functional assemblies
Quaternary Structure: Multimeric Proteins or Functional Assemblies
  • Multimeric Proteins
  • Macromolecular Assemblies

Ribosome:Protein Synthesis

Hemoglobin:

A tetramer

Replisome:

DNA copying

protein folding
Protein Folding
  • The amino-acid sequence of a protein determines the 3D fold [Anfinsen et al., 1950s]

Some exceptions:

    • All proteins can be denatured
    • Some proteins have multiple conformations
    • Some proteins get folding help from chaperones
  • The function of a protein is determined by its 3D fold
  • Can we predict 3D fold of a protein given its amino-acid sequence?
the leventhal paradox
The Leventhal Paradox
  • Given a small protein (100aa) assume 3 possible conformations/peptide bond
  • 3100 = 5 × 1047 conformations
  • Fastest motions 10- 15 sec so sampling all conformations would take 5 × 1032 sec
  • 60 × 60 × 24 × 365 = 31536000 seconds in a year
  • Sampling all conformations will take 1.6 × 1025 years
  • Each protein folds quickly into a single stable native conformation ­ the Leventhal paradox
the hydrophobic effect
The Hydrophobic Effect
  • Important for folding, because every amino acid participates!

Fauchere and Pilska (1983). Eur. J. Med. Chem. 18, 369-75.

Experimentally Determined Hydrophobicity Levels

protein structure determination
Protein Structure Determination
  • Experimental
    • X-ray crystallography
    • NMR spectrometry
  • Computational – Structure Prediction

(The Holy Grail)

Sequence implies structure, therefore in principle we can predict the structure from the sequence alone

protein structure prediction
Protein Structure Prediction
  • ab initio
    • Use just first principles: energy, geometry, and kinematics
  • Homology
    • Find the best match to a database of sequences with known 3D-structure
  • Threading
  • Meta-servers and other methods
ab initio prediction
Ab initio Prediction
  • Sampling the global conformation space
    • Lattice models / Discrete-state models
    • Molecular Dynamics
    • Pre-set libraries of fragment 3D motifs
  • Picking native conformations with an energy function
    • Solvation model: how protein interacts with water
    • Pair interactions between amino acids
  • Predicting secondary structure
    • Local homology
    • Fragment libraries
lattice string folding
Lattice String Folding
  • HP model: main modeled force is hydrophobic attraction
    • NP-hard in both 2-D square and 3-D cubic
    • Constant approximation algorithms
    • Not so relevant biologically
rosetta http www bioinfo rpi edu bystrc hmmstr server php

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ROSETTAhttp://www.bioinfo.rpi.edu/~bystrc/hmmstr/server.php

http://depts.washington.edu/bakerpg/papers/Bonneau-ARBBS-v30-p173.pdf

  • Monte Carlo based method
  • Limit conformational search space by using sequence—structure motif I-Sites library (http://isites.bio.rpi.edu/Isites/)
    • 261 patterns in library
    • Certain positions in motif favor certain residues
  • Remove all sequences with <25% identity
  • Find structures of the 25 nearest sequence neighbors of each 9-mer

Rationale

    • Local structures often fold independently of full protein
    • Can predict large areas of protein by matching sequence to I-Sites
i sites examples
Non polar helix

Abundance of alanine at all positions

Non-polar side chains favored at positions 3, 6, 10 (methionine, leucine, isoleucine)

I-Sites Examples
  • Amphipathic helix
    • Non-polar side chains favored at positions 6, 9, 13, 16 (methionine, leucine, isoleucine)
    • Polar side chains favored at positions 1, 8, 11, 18 (glutamic acid, lysine)
rosetta method

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ROSETTA Method
  • New structures generated by swapping compatible fragments
  • Accepted structures are clustered based on energy and structural size
  • Best cluster is one with the greatest number of conformations within 4-Å rms deviation structure of the center
  • Representative structures taken from each of the best five clusters and returned to the user as predictions
rosetta results
Rosetta Results
  • In CASP4, Rosetta’s best models ranged from 6–10 Å rmsd C
  • For comparison, good comparative models give 2-5 Å rmsd C
  • Most effective with small proteins (<100 residues) and structures with helices
the scop database
The SCOP Database

Structural Classification Of Proteins

FAMILY: proteins that are >30% similar, or >15% similar and have similar known structure/function

SUPERFAMILY: proteins whose families have some sequence and function/structure similarity suggesting a common evolutionary origin

COMMON FOLD: superfamilies that have same secondary structures in same arrangement, probably resulting by physics and chemistry

CLASS: alpha, beta, alpha–beta, alpha+beta, multidomain

status of protein databases
Status of Protein Databases

PDB

SCOP: Structural Classification of Proteins. 1.67 release24037 PDB Entries (15 May 2004). 65122 Domains.

EMBL

evolution of proteins domains
Evolution of Proteins – Domains
  • #members in different families obey power law
  • 429 families common in all 14 eukaryotes;
  • 80% of animal domains, 90% of fungi domains
  • 80% of proteins are multidomain in eukaryotes;
  • domains usually combine pairwise in same order --why?

Chothia, Gough, Vogel, Teichmann, Science 300:1701-17-3, 2003

Evolution of proteins happens mainly through duplication, recombination, and divergence

homology based prediction
Homology-based Prediction
  • Align query sequence with sequences of known structure, usually >30% similar
  • Superimpose the aligned sequence onto the structure template, according to the computed sequence alignment
  • Perform local refinement of the resulting structure in 3D

The number of unique structural folds

is small (possibly a few thousand)

90% of new structures submitted to PDB in the

past three years have similar folds in PDB

homology based prediction38

Raw model

Loop modeling

Side chain placement

Refinement

Homology-based Prediction