Mercurial > repos > bgruening > openbabel_spectrophore_search
changeset 7:445ee18e8d4c draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/chemicaltoolbox/openbabel commit ed9b6859de648aa5f7cde483732f5df20aaff90e
| author | bgruening |
|---|---|
| date | Tue, 07 May 2019 13:22:45 -0400 |
| parents | 03f2abc862b4 |
| children | 867fa18875b9 |
| files | macros.xml ob_spectrophore_search.xml test-data/2_mol.dat test-data/CO.smarts |
| diffstat | 4 files changed, 16 insertions(+), 15 deletions(-) [+] |
line wrap: on
line diff
--- a/macros.xml Mon Sep 03 16:35:07 2018 -0400 +++ b/macros.xml Tue May 07 13:22:45 2019 -0400 @@ -1,9 +1,10 @@ <macros> - <token name="@VERSION@">2.4.1</token> + <token name="@VERSION@">2.4.2</token> <xml name="requirements"> <requirements> <requirement type="package" version="2.4.1">openbabel</requirement> + <requirement type="package" version="3">python</requirement> <yield /> </requirements> </xml> @@ -37,6 +38,3 @@ </citations> </xml> </macros> - - -
--- a/ob_spectrophore_search.xml Mon Sep 03 16:35:07 2018 -0400 +++ b/ob_spectrophore_search.xml Tue May 07 13:22:45 2019 -0400 @@ -1,10 +1,10 @@ -<tool id="openbabel_spectrophore_search" name="Spectrophores(TM) search:" version="@VERSION@.0"> - <description>similarity search based on 1D chemical features</description> +<tool id="openbabel_spectrophore_search" name="Spectrophores search" version="@VERSION@.0"> + <description>- similarity search based on 1D chemical features</description> <macros> <import>macros.xml</import> </macros> <expand macro="requirements"> - <requirement type="package" version="1.7.1">numpy</requirement> + <requirement type="package" version="1.16.2">numpy</requirement> </expand> <command detect_errors="aggressive"> <![CDATA[ @@ -17,10 +17,10 @@ </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)"/> + label="Target molecule in SDF format (it must contain Spectrophores 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" + label="Tabular file with pre-computed Spectrophores in one column"/> + <param name="column" label="Specify the column number containing the Spectrophores descriptors" type="data_column" data_ref="library" accept_default="true" /> </inputs> <outputs> @@ -41,10 +41,10 @@ **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. +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. + |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 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. @@ -53,15 +53,14 @@ - |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)| can be computed rapidly -.. |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. +**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. ----- @@ -91,6 +90,7 @@ .. _`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 +.. |Spectrophores (TM)| unicode:: Spectrophores U+2122 ]]> </help>