Superposition

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Superposition Threading

• Gary Van Domselaar
• University of Alberta
• gary.vandomselaar_at_ualberta.ca

Slides adapted from David Wishart
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Outline

• Vectors, matrices and other geometry issues
• General Superposition concepts
• Threading and threading methods

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Vectors Define Bonds and Atomic Positions
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Review - Vectors
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Review - Vectors

• Vectors can be added together
• Vectors can be subtracted
• Vectors can be multiplied (dot or cross or by a
  matrix)
• Vectors can be transformed (resized)
• Vectors can be translated
• Vectors can be rotated

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Matrices

• A matrix is a table or array of characters
• A matrix is also called a tensor of rank 2

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Different Types of Matrices
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Different Types of Matrices
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Review - Matrix Multiplication
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Rotation
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Rotation
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Rotation
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Rotation (Detail)
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Superposition

• Objective is to match or overlay 2 or more
  similar objects
• Requires use of translation and rotation
  operators (matrices/vectors)
• Recall that very three dimensional object can be
  represented by a plane defined by 3 points

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Superposition
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Superposition
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Superposition
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Superposition
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Superposition
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Superposition
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Superposition
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Superposition
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Superposition
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Superposition
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Returning to the red frame
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Returning to the red frame

• Begin with the superimposed structures on the x-y
  plane
• Apply counterclockwise rot. By ?
• Apply counterclockwise rot. By ?
• Apply counterclockwise rot. By ?
• Apply red translation to red origin

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Superposition - Applications

• Ideal for comparing or overlaying two or more
  protein structures
• Allows identification of structural homologues
  (CATH and SCOP)
• Allows loops to be inserted or replaced from loop
  libraries (comparative modelling)
• Allows side chains to be replaced or inserted
  with relative ease

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Side Chain Placement
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Amino Acid Side Chains
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Adding a Side Chain
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Adding a Side Chain
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Adding a Side Chain
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Adding a Side Chain
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Adding a Side Chain
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Superposition

• The concept of superposition is key to many
  aspects of protein structure generation and
  comparison
• Superposition may be used to insert side chains
  and loops (for homology models)
• Side chains require more consideration as side
  chain packing ultimately determines the 3D
  structure of proteins

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Superposition - RMSD

• The degree of similarity between two or more
  structures is described by its average root mean
  square deviation (RMSD)

x3
x4
x2
y3
y4
y2
x5
y5
x1
x1
y1
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Superposition Software

• Swiss PDB Viewer
• Aligns 2 homologous structures

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Superposition Software

• CE Structure Comparison by Combinatorial
  Extension
• http//cl.sdsc.edu/ce.html
• Superposition for 2 chains and for multiple
  chains (new)

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Superposition Software

• SuperPose
• http//wishart.biology.ualberta.ca/SuperPose/
• Superposition for 2 chains and for multiple
  chains
• Subdomain superposition
• Superposition of structures with low sequence
  identity

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Definition

• Threading - A protein fold recognition technique
  that involves incrementally replacing the
  sequence of a known protein structure with a
  query sequence of unknown structure. The new
  model structure is evaluated using a simple
  heuristic measure of protein fold quality. The
  process is repeated against all known 3D
  structures until an optimal fit is found.

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Why Threading?

• Secondary structure is more conserved than
  primary structure
• Tertiary structure is more conserved than
  secondary structure
• Therefore very remote relationships can be better
  detected through 2o or 3o structural homology
  instead of sequence homology

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Visualizing Threading
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Visualizing Threading
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Visualizing Threading
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Visualizing Threading
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Visualizing Threading
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Threading

• Database of 3D structures and sequences
• Protein Data Bank (or non-redundant subset)
• Query sequence
• Sequence lt 25 identity to known structures
• Alignment protocol
• Dynamic programming
• Evaluation protocol
• Distance-based potential or secondary structure
• Ranking protocol

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2 Kinds of Threading

• 2D Threading or Prediction Based Methods (PBM)
• Predict secondary structure (SS) or ASA of query
• Evaluate on basis of SS and/or ASA matches
• 3D Threading or Distance Based Methods (DBM)
• Create a 3D model of the structure
• Evaluate using a distance-based hydrophobicity
  or pseudo-thermodynamic potential

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2D Threading Algorithm

• Convert PDB to a database containing sequence, SS
  and ASA information
• Predict the SS and ASA for the query sequence
  using a high-end algorithm
• Perform a dynamic programming alignment using the
  query against the database (include sequence, SS
  ASA)
• Rank the alignments and select the most probable
  fold

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Database Conversion
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-
-
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2o Structure Identification

• DSSP - Database of Secondary Structures for
  Proteins (swift.embl-heidelberg.de/dssp)
• VADAR - Volume Area Dihedral Angle Reporter
  (redpoll.pharmacy.ualberta.ca)
• PDB - Protein Data Bank (www.rcsb.org)

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ASA Calculation

• DSSP - Database of Secondary Structures for
  Proteins (swift.embl-heidelberg.de/dssp)
• VADAR - Volume Area Dihedral Angle Reporter
  (www.redpoll.pharmacy.ualberta.ca/vadar/)
• GetArea - www.scsb.utmb.edu/getarea/area_form.html
  

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Other ASA sites

• Connolly Molecular Surface Home Page
• http//www.biohedron.com/
• Naccess Home Page
• http//sjh.bi.umist.ac.uk/naccess.html
• ASA Parallelization
• http//cmag.cit.nih.gov/Asa.htm
• Protein Structure Database
• http//www.psc.edu/biomed/pages/research/PSdb/

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2D Threading Algorithm

• Convert PDB to a database containing sequence, SS
  and ASA information
• Predict the SS and ASA for the query sequence
  using a high-end algorithm
• Perform a dynamic programming alignment using the
  query against the database (include sequence, SS
  ASA)
• Rank the alignments and select the most probable
  fold

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ASA Prediction

• PredictProtein-PHDacc (58)
• http//cubic.bioc.columbia.edu/predictprotein
• PredAcc (70?)
• condor.urbb.jussieu.fr/PredAccCfg.html

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2D Threading Algorithm

• Convert PDB to a database containing sequence, SS
  and ASA information
• Predict the SS and ASA for the query sequence
  using a high-end algorithm
• Perform a dynamic programming alignment using the
  query against the database (include sequence, SS
  ASA)
• Rank the alignments and select the most probable
  fold

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Sij (Identity Matrix)
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A Simple Example...
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Lets Include 2o info ASA
Sij k1Sij k2Sij k3Sij
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A Simple Example...
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2D Threading Performance

• In test sets 2D threading methods can identify
  30-40 of proteins having very remote homologues
  (i.e. not detected by BLAST) using minimal
  non-redundant databases (lt700 proteins)
• If the database is expanded 4x the performance
  jumps to 70-75
• Performs best on true homologues as opposed to
  postulated analogues

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2D Threading Advantages

• Algorithm is easy to implement
• Algorithm is very fast (10x faster than 3D
  threading approaches)
• The 2D database is small (lt500 kbytes) compared
  to 3D database (gt1.5 Gbytes)
• Appears to be just as accurate as DBM or other 3D
  threading approaches
• Very amenable to web servers

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Servers - PredictProtein
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Servers - 123D
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Servers - GenThreader
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More Servers - www.bronco.ualberta.ca
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2D Threading Disadvantages

• Reliability is not 100 making most threading
  predictions suspect unless experimental evidence
  can be used to support the conclusion
• Does not produce a 3D model at the end of the
  process
• Doesnt include all aspects of 2o and 3o
  structure features in prediction process
• PSI-BLAST may be just as good (faster too!)

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Making it Better

• Include 3D threading analysis as part of the 2D
  threading process -- offers another layer of
  information
• Include more information about the coil state
  (3-state prediction isnt good enough)
• Include other biochemical (ligands, function,
  binding partners, motifs) or phylogenetic
  (origin, species) information

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3D Threading Servers

• Generate 3D models or coordinates of possible
  models based on input sequence
• Loopp (version 2)
• http//ser-loopp.tc.cornell.edu/loopp.html
• 3D-PSSM
• http//www.sbg.bio.ic.ac.uk/3dpssm/
• All require email addresses since the process may
  take hours to complete

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