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Practical Innovation at BioCon 2003


Protein Structure Analysis: A Tools Approach
William†Gleason, University of Minnesota
Eric A.†Johnson

Track: Bioinformatics 2003 Tutorial
Date: Monday, February 03
Time:†8:30am - 12:00pm
Location:†California Ballroom A

Three-dimensional data for proteins is available freely via the Web from the Protein Data Bank (PDB) located at Rutgers University. Gleasonís tutorial acquaints attendees with protein structure, outlines experimental methods for determining structure, and takes a tools approach toward the analysis of protein structural data. Specific topics include:

I. Protein structure: An Introduction
The first hour presents material appropriate for someone who has very little background in the area of protein structure, in a way that prepares attendees for subsequent discussion of tools and applications, and approximates what can be found scattered in introductory biochemistry texts.

II. Where do PDB (protein data base) files come from?
The two most commonly used methods for three-dimensional structure determination (X-ray crystallography and NMR spectroscopy)are briefly discussed, including limitations and ambiguities of the experimental data in pdb files, as well as the Cambridge Structural Data Base (small molecule database).

III. Protein structure analysis: a tools approach
The enormous information content of a three-dimensional protein structure requires tools for both analysis and quality evaluation. Gleason gives some examples of such tools: PAP ( protein analysis package), PROCHECK (protein check), PLATON (small molecule evaluation), LIGPLOT (analysis of protein-small molecule interactions). Molecular visualization tools will also be briefly discussed: UCSF MidasPlus, SwissPDBViewer, MolMol, VMD.

IV. Case Studies
a. Docking of an HIV-protease inhibitor
b. Homology modelling: FGF - done on the Web with SwissPDB vs. "more sophisticated" approaches.
c. NAMD/VMD - scaleable molecular dynamics calculations on a large Linux cluster Heparin/FGF interactions, strategies for semi-automated generation of input and analysis of output.

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