Add simorgh

tools/simorgh/.shed.yml

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+name: simorgh
+owner: bgruening
+description: Apo-State and Cryptic Ligand Binding Site Prediction
+homepage_url: https://github.com/amisteromid/SIMORGH
+long_description: |
+  SIMORGH is a deep learning-based method for predicting apo-state and cryptic ligand binding sites in proteins. It leverages SE(3) equivariant neural networks to accurately identify potential binding pockets. This tool is particularly useful for drug discovery, where understanding the dynamic nature of protein structures is crucial.
+remote_repository_url: https://github.com/bgruening/galaxytools/tree/master/tools/simorgh
+type: unrestricted
+categories:
+  - Computational chemistry
+  - Molecular Dynamics

tools/simorgh/macros.xml

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+<macros>
+    <token name="@TOOL_VERSION@">1.0.0</token>
+    <token name="@VERSION_SUFFIX@">0</token>
+    <token name="@PROFILE@">25.0</token>
+    <xml name="requirements">
+        <requirements>
+            <container type="docker">
+                ghcr.io/amisteromid/simorgh:latest
+            </container>
+        </requirements>
+    </xml>
+    <xml name="creators">
+        <creator>
+            <person givenName="Amirhossein" familyName="Naghsh Nilchi" email="nilchia@informatik.uni-freiburg.de" identifier="https://orcid.org/0000-0003-1329-3044"/>
+            <person givenName="Omid" familyName="Mokhtari" email="omid.mokhtari@inria.fr" identifier="https://orcid.org/0009-0000-8751-8117"/>
+            <person givenName="Hamed" familyName="Khakzad" email="hamed.khakzad@inria.fr" identifier="https://orcid.org/0000-0002-8556-0650"/>
+            <person givenName="Björn" familyName="Grüning" email="gruening@informatik.uni-freiburg.de" identifier="https://orcid.org/0000-0002-3079-6586"/>
+        </creator>
+    </xml>
+    <xml name="edam">
+        <edam_topics>
+            <edam_topic>topic_2814</edam_topic>
+            <!-- Protein structure analysis -->
+            <edam_topic>topic_0123</edam_topic>
+            <!-- Protein properties -->
+            <edam_topic>topic_0081</edam_topic>
+            <!-- Structure analysis -->
+            <edam_topic>topic_3336</edam_topic>
+            <!-- Drug discovery -->
+            <edam_topic>topic_3474</edam_topic>
+            <!-- Machine learning -->
+        </edam_topics>
+        <edam_operations>
+            <edam_operation>operation_0250</edam_operation>
+            <!-- Protein property calculation -->
+            <edam_operation>operation_2406</edam_operation>
+            <!-- Protein structure analysis -->
+        </edam_operations>
+    </xml>
+    <xml name="citations">
+        <citations>
+            <citation type="bibtex">
+                @unpublished{SIMORGH2026,
+                    author = {Omid Mokhtari, et al.},
+                    title = {SIMORGH: Ensemble-Aware Geometric Deep Learning for Apo-State and Cryptic Ligand Binding Site Prediction},
+                    year = {2026},
+                    url = {https://github.com/amisteromid/SIMORGH}
+                }
+            </citation>
+            <yield/>
+        </citations>
+    </xml>
+</macros>