view search/ob_spectrophore_search.xml @ 10:cc63a42fd22e

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<tool id="ctb_spectrophore_search" name="Spectrophores(TM) search:" version="1.0">
  <description>similarity search based on 1D chemical features</description>
  <requirements>
    <requirement type="package" version="2.3.2">openbabel</requirement>
    <requirement type="package" version="1.7.1">numpy</requirement>
  </requirements>
  <command interpreter="python">
    ob_spectrophore_search.py
      --target $target
      --library $library
      --output $outfile
      --column $column
  </command>
  <inputs>
    <param name="target" type="data" format="sdf" label="Target molecule in SDF format (it must contain its Spectrophores(TM) stored as meta-data)"/>
    <param name="library" type="data" format="tabular" label="Tabular file with pre-computed Spectrophores(TM) in one column"/>
    <param name="column" label="Specify the column number containing the Spectrophores(TM) descriptors" type="data_column" data_ref="library" accept_default="true" />
  </inputs>
  <outputs>
    <data format="tabular" name="outfile"/>
  </outputs>
  <tests>
    <test>
        <param name="target" ftype="sdf" value="CID2244_with_spectrophore.sdf"/>
        <param name="library" value="lib.tabular" />
        <param name="column" value="8" />
        <output name="outfile" ftype="tabular" file="ob_spectrophore_search.tabular" />
    </test>
  </tests>
  <help>

.. class:: infomark

**What does this tool do?**

  This tool computes the Euclidean distance between the Spectrophores(TM) descriptors of the target to each molecule stored in the library.

-----

.. class:: warningmark

**Tip:** this tool is useful to select compounds with similar chemical features to a target, but accounting for the discovery of diverse scaffolds. This is in contrast to the results expected in a similarity search based on atom connectivity.

**Hint:** the target molecule MUST BE an sdf formatted file with the Spectrophores(TM) descriptors stored as meta-data. Such file can be generated using the "Compute physico-chemical properties" tool.

**Hint:** the library of compounds is a tabular formatted file with 1 line / compound. One column contains the Spectrophores(TM) descriptors.

-----

.. class:: infomark

**Spectrophores(TM)** are Silicos' screening technology which converts three-dimensional molecular property data into one-dimensional spectra. Typical characteristics that can be converted include electrostatic potentials, molecular shape, lipophilicity, hardness and softness potentials. The computation of Spectrophores(TM) is independent of the position and orientation of a molecule and this allows to easily compare Spectrophores(TM) of different molecules.

Molecules with similar three-dimensional properties and shape, and therefore also similar biological activities, always have similar Spectrophores(TM), and as a result this technique is very powerful as a tool to investigate the similarity of molecules and can be applied as a screening tool for molecular databases, virtual screening, and databse characterisations.

**Advantages:**

    * Spectrophores(TM) can realistically compute ligand-protein interactions based on aforementioned molecular descriptors.
    * Spectrophores(TM) can be applied in both a ligand- or target-based setting.
    * Spectrophores(TM) can distinguish, if needed, between the different enantiomers of stereo-selective compounds.
    * Spectrophores(TM) can be computed fast.

Information extracted from the Silico's website: http://www.silicos.be/technologies/spectrophore

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**This tool uses Pybel:** N. M. O'Boyle, C. Morley and G. R. Hutchison. Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit Chem. Cent. J. 2008, 2, 5.

**Spectrophores(TM)** is a registered tool implemented in the open-source OpenBabel. Copyright (C) 2005-2011 by Silicos NV.

  </help>
</tool>