<tool id="sucos_docking_scoring" name="Score docked poses using SuCOS" version="0.1">
    <description>- compare shape and feature overlap of docked ligand poses to a reference molecule</description>
    <macros>
        <import>sucos_macros.xml</import>
    </macros>
    <expand macro="requirements"/>
    <command detect_errors="aggressive"><![CDATA[
        python '$__tool_directory__/sucos.py'
            -i '$input'
            -r '$refmol'
            -o '$output'
            --refmol-format mol
            $tanimoto
    ]]></command>
    <inputs>
        <param type="data" name="input" format="sdf" label="Ligands to be scored" help="Input in SDF format." />
        <param type="data" name="refmol" format="sdf,mol" label="Reference molecule to overlay" help="Input in SDF or MOL format." />
        <param type="boolean" name="tanimoto" truevalue="--tanimoto" falsevalue="" label="Include Tanimoto calculations" help="Whether to handle the distance as Tanimoto." />
    </inputs>
    <outputs>
        <data format="sdf" name="output" label="The scored ligands"/>
    </outputs>
    <tests>
        <test>
            <param name="input" ftype="sdf" value="sucos_inputs.sdf"/>
            <param name="refmol" ftype="mol" value="sucos_refmol.mol"/>
            <output name="output" ftype="sdf">
                <assert_contents>
                    <has_text text="SuCOS_Score" />
                </assert_contents>
            </output>
        </test>
    </tests>
    <help><![CDATA[
.. class:: infomark

**What it does**

This tool determines the shape and feature overlap of docked ligand poses compared to a reference molecule, usually a known ligand.
The RDKit FeatureMap functionality is used to do the scoring.

The original SuCOS code is on GitHub_ under a MIT license. The SuCOS work is described here_.

.. _GitHub: https://github.com/susanhleung/SuCOS
.. _here: https://chemrxiv.org/articles/SuCOS_is_Better_than_RMSD_for_Evaluating_Fragment_Elaboration_and_Docking_Poses/8100203

.. class:: infomark

**Input**

Molecules such as an SD file dataset from the history.

.. class:: infomark

**Output**

The same SD file with a "SuCOS_Score" property added. A score of 1.0 infers a perfect overlap, a score of 0.0 no overlap.
A rule of thumb is that poses with a score greater than 0.5 can be be considered "useful".

    ]]></help>
    <expand macro="citations"/>
</tool>