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Tertiary protein structure viewing and prediction. July 3, 2007 Learning objectives- Learn how to manipulate protein structures with Deep View software. Learn the steps to protein structure modeling with Deep View. Workshop-Manipulation of the lysozyme and hemoglobin.

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tertiary protein structure viewing and prediction
Tertiary protein structure viewing and prediction
  • July 3, 2007
  • Learning objectives- Learn how to manipulate protein structures with Deep View software. Learn the steps to protein structure modeling with Deep View.
  • Workshop-Manipulation of the lysozyme and hemoglobin.
protein structure viewers
Protein structure viewers
  • RasMol
  • Deep View
  • Cn3D
  • WebLabViewer
  • Chimera
steps to tertiary structure prediction
Steps to tertiary structure prediction
  • Comparative protein modeling
    • Extrapolates a new structure based on solved structures that are related by sequence.
  • Steps for SWISS-Model
    • Identification of modeling templates.
    • Alignment between target and templates.
    • Model building.
    • Evaluation.
step 1 identification of modeling templates
Step 1: Identification of modeling templates
  • One chooses a cutoff value from FastA or BLAST search ( E<10-5) and perform BLAST search of Protein Data Bank.
  • Up to ten structure templates can be used but the one with the highest sequence similarity to the target sequence (lowest E-value) is designated as the reference template. Its structure is given the most weight.
  • Ca atoms of the templates are selected for superimposition.
    • This generates a structurally corrected multiple sequence alignment
step 2 alignment
Step 2: Alignment
  • Up to 5 template structures are superimposed.
  • Incompatible templates are removed.
  • Pairwise alignment is created between target and main template structures.
step 3 building the model
Step 3: Building the model
  • Framework construction
    • Average the position of each atom in target sequence, based on the corresponding atoms in template (start with C  atoms)
  • Each loop is defined by the length of the
  • loop and C atom coordinates of the four residues preceding
  • and following the loop. Constraint space programming is used.
  • Portions of the target sequence that do not match the
  • template are constructed from a “spare part” algorithm.
step 3 building the model8
Step 3: Building the model
  • Completing the backbone-a library of PDB entries is consulted to add carbonyl groups and amino groups. The 3-D coordinates come from a separate library of pentapeptide backbone fragments. These backbone fragments are fitted onto the target C alpha carbons. The central tri-peptide atoms are averaged from each backbone atom (N,C,C(O)).
  • Side chains are added from a table of most probable rotamers given a certain backbone conformation.
step 4 energy minimization
Step 4: Energy Minimization

Model refinement-minimization of energy (GROMOS96 force field)