view search/ob_spectrophore_search.xml @ 2:125da3a296ca draft default tip

Uploaded

<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">
<![CDATA[
    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>
<![CDATA[

.. 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.

|Spectrophores (TM)| search
		|Spectrophores (TM)| is a screening technology by Silicos_ 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 is independent of the position and orientation of a molecule and allows an easy comparison of |Spectrophores (TM)| of different molecules.

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

.. |Spectrophores (TM)| unicode:: Spectrophores U+2122

-----

.. class:: warningmark

**Hint** 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.

-----

.. class:: infomark

**Input**

The target molecule must be a SD formatted file with the |Spectrophores (TM)| descriptors stored as metadata. Such files can be generated using the *Compute physico-chemical properties* tool.

-----

.. class:: infomark

**Output**

The library of compounds is a tabular file with one line per compound. One column contains the |Spectrophores (TM)| descriptors.

-----

.. class:: infomark

**Cite**

N M O'Boyle, C Morley and G R Hutchison - `Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit`_

Silicos_ - |Spectrophores (TM)| is a registered tool implemented in the open-source OpenBabel.

.. _`Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit`: http://www.biomedcentral.com/content/pdf/1752-153X-2-5.pdf
.. _Silicos: http://openbabel.org/docs/dev/Fingerprints/spectrophore.html

]]>
  </help>
</tool>