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Secondary Target Identification for Neuraminidase Inhibitor Drugs

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SMAP (SOIPPA Algorithm): Target the 'druggable' human proteome with known ... Summer Palace. ???. Lao She Tea House ????. Beijing Zoo. ?????. Badminton ??? ... – PowerPoint PPT presentation

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Title: Secondary Target Identification for Neuraminidase Inhibitor Drugs


1
Secondary Target Identification for Neuraminidase
Inhibitor Drugs
  • Michael Wang
  • PRIME
  • July 18, 2008
  • Computer Network Information Center
  • Beijing, China

2
Project Goals
  • Strategy for secondary target identification
  • SMAP (SOIPPA Algorithm) Target the druggable
    human proteome with known structural homologues
  • TarFisDock
  • Program simulates binding of drugs to database
    proteins
  • Proteins are ranked based on best energetic
    interactions
  • Disadvantage does not take into account protein
    flexibility
  • To take advantage of Autodock4s flexible
    receptor feature to support receptor flexibility.
    To refine the target selection criteria by
    ensuring the proper parameterization of the
    druggable proteome.  Additionally, I will use
    known NA inhibitors and all known neuraminidases
    from different species, especially humans, with
    crystal structures as my initial test set.
  • Selectivity of known Neuraminidase Inhibitors
    against viral subtypes
  • Make comparative studies of the NA inhibitors
    against other potentially pandemic subtypes, such
    as N2, N7
  • Classify the previously identified top 27 hits in
    terms of their specificity for group-1, group-2
    enzymes, and in particular the N2 and N7 enzymes
  • Use Autodock4 to establish the parameters for
    optimal binding conditions through redocking of
    ligands from known crystal structures, using
    conditions previously characterized for N1 as a
    starting point.
  • Neuraminidase virtual screening hits and
    Polymorphism
  • Study the effects of polymorphism in
    neuraminidase and examine the interaction of
    oseltamivir with the R41Q mutant, situated near
    the active site of sialic acid, by using Autodock
    and Modeler
  • Confirm validity using Procheck, WHATIF, and
    SCWRL to examine the selectivity for different
    neuraminidases inhibitors with this particular
    phenotype

3
Progress
  • Obtained a list of druggable human proteins from
    Jacob Durrant
  • Got SMAP to run successfully after editing
    scripts and revising commands
  • Finished setting up SMAP environment by changing
    parameters in .sh shell script
  • Edited parameters in pdbdefault.properties and
    smap.properties
  • Recompiled qhull source code and placed it in the
    qhull linux directory within the SMAP
    distribution
  • Installed and configured JDK 1.6 on the server
  • Completed setup for MySQL database in order to
    match known ligand-binding sites
  • Contacted Dr. Lei Xie regarding running larger
    datasets for SMAP
  • Emailed developers of Autodock regarding program
    compatibility with different operating systems

4
Work to be done
  • Figure out how to run SMAP by setting the query
    output with the druggable human proteome instead
    of with a single query chain
  • Analyze and understand the resulting output
    values for SMAP results
  • Create an Excel Spreadsheet for a data
    compilation of structural alignment between
    ligand-binding sites, Z-scores, Raw-scores,
    Tanimoto Coefficients and RMSD values
  • Successfully load Autodock Tools on my OS in
    preparation for evaluating optimal binding
    conditions of neuraminidase inhibitor drugs and
    neuraminidases
  • Generate mol2 file for oseltamivir and other
    inhibitor drugs in preparation for reverse
    docking analysis through TarFisDock web service.

5
Summer Palace ???
6
Lao She Tea House ????
7
Beijing Zoo ?????
Badminton ???
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