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Methods of Modeling Protein Structure

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Comparative Modeling based on similarities from evolution ... After finding similar sequences, a structure is modeled using that related sequence. ... – PowerPoint PPT presentation

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Title: Methods of Modeling Protein Structure


1
Methods of ModelingProtein Structure
  • Peter Bell
  • December 6, 2002

2
3-D Structure of Proteins
  • Structure of natural proteins guided by 2 sets of
    principles on vastly different time scales
  • Laws of Physics
  • Chemical bonds, H-bonds, electonic interactions
  • Theory of Evolution
  • Families of similar proteins share similar
    sequences, structure, and often function

3
Modeling Proteins
  • Two general methods to modeling
  • Each based on either of the principles governing
    3-D structure
  • Comparative Modeling based on similarities from
    evolution
  • De novo or ab initio based on physicsenergies

4
Comparative Methods
  • Four Main Steps in this process
  • Finding known structures related to the target
    sequence being modeled. (finding templates)
  • Aligning sequence with known structures
  • Building a model
  • Assesing the model

5
Comparative Modeling
  • Finding Templates
  • 3-D structures are more conserved that primary
    sequences through evolution
  • Proteins with similar sequences will often share
    structural characteristicsfind using sequence
    comparison methods such as PSI-BLAST
  • Sometimes, very different sequences will share
    structurefind these using the Protein Data Bank
    (makes use of coarse structures for quick
    comparisons)

6
Comparative Modeling
  • Building the model
  • After finding similar sequences, a structure is
    modeled using that related sequence.
  • Core regions are kept intact (helices, sheets)
  • Loops and side chains using various methods to
    minimize energies in the presence of the core
    regions.
  • Three main methods
  • Loops and side chains based on alignment to
    related sequences in other proteins
  • Approx. position of atoms is calculated from
    approx. position of conserved atoms in template.
  • Distance Geometry or spatial restraints are
    optimized

7
Comparative Modeling
  • Assesing the Model
  • Accuracy associated with the percent of the
    sequence that matches the template
  • Most errors in side chains or in loops
  • These are mostly insignificant as these parts
    dont effect function.
  • Other errors include small shifts and distortions
    in other parts of the protein
  • Error increases rapidly below 30 sequence
    similarity

8
De novo Prediction
  • Can be done with any proteinno other members of
    the family need be known
  • Based on assumption Native State is at the
    global free energy minimum
  • A large scale search is carried out to find this
    minimum with tertiary structure.

9
De novo Prediction
  • Two key components in finding minimum
  • Methods for carrying out search efficiently
  • Free energy function used to calculate energy
  • Complexity of these increases as computing power
    increases
  • Often only a subset of actual atoms in a protein
    is modeled (leave out hydrogen, for example)
  • The potential functions must then account for
    these absent atoms.
  • Some newer methods flip certain sequences into
    possible secondary structures, calculate energy,
    then find how these fit into tertiary structure

10
De novo Prediction
  • Accuracy is much lower than comparative methods
    (with gt30 sequence similarity)
  • Basic structure can still be determined
    reasonably well with 150 amino acids or less
  • Accuracy too low if high-resolution info is
    needed.
  • Low-resolution info is useful in finding
    structural and functional relationships no
    apparent by comparison of AA sequence.

11
Summary
  • Two methods available to model proteins based on
    their AA sequence
  • Comparative Theory of Evolution
  • De novo Laws of Physics
  • Comparative more accuratebut requires other
    structures to be known
  • De novo can be used for any protein but requires
    more computing power and wont produce highly
    accurate models.

12
References
  • Baker, D. Sali, A. Protein Structure Prediction
    and Structural Genomics. Science 2001, 294,
    93-96.
  • Fiser, A. Feig, M. Brooks, C. L. Sali, A.
    Evolution and Physics in Comparative Protein
    Structure Modeling. Acc. Chem. Res. 2002, 35,
    413-421.
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