feat: add interpro searcher

examples/input_examples/search_interpro_demo.jsonl

@@ -0,0 +1,3 @@
+{"type": "protein", "content": "P01308"}
+{"type": "protein", "content": "Q96KN2"}
+{"type": "protein", "content": "MGHHHHHHHGSSGVDLGTENLYFQSNAMDFPQQLEACVKQANQALSRFIAPLPFQNTPVVETMQYGALLGGKRLRPFLVYATGHMFGVSTNTLDAPAAAVECIHAYSLIHDDLPAMDDDDLRRGLPTCHVKFGEANAILAGDALQTLAFSILSDANMPEVSDRDRISMISELASASGIAGMCGGQALDLDAEGKHVPLDALERIHRHKTGALIRAAVRLGALSAGDKGRRALPVLDKYAESIGLAFQVQDDILDVVGDTATLGKRQGADQQLGKSTYPALLGLEQARKKARDLIDDARQALKQLAEQSLDTSALEALADYIIQRNK"}

examples/search/search_protein/search_interpro/README.md

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+# Search Protein Domains with InterPro
+
+This example demonstrates how to search for protein domain information and functional annotations using the InterPro database.
+
+## Overview
+
+The InterPro search pipeline reads protein queries (UniProt accession numbers or protein sequences) and searches the InterPro database to find domain matches, functional annotations, GO terms, and pathways.
+
+InterPro supports two search modes:
+1. **UniProt Accession Lookup**: Fast lookup of pre-computed domain information for known UniProt entries
+2. **Protein Sequence Analysis**: Submit protein sequences for InterProScan analysis to discover domains
+
+## Quick Start
+
+### 1. Configure Search Parameters
+
+Edit `search_interpro_config.yaml` to set:
+
+- **Input file path**: Set the path to your protein sequence or UniProt ID queries
+- **InterPro parameters**:
+  - `email`: Your email address for EBI API requests (required)
+  - `api_timeout`: Request timeout in seconds (default: 30)
+
+Example configuration:
+```yaml
+input_path:
+  - examples/input_examples/search_interpro_demo.jsonl
+
+data_sources: [interpro]
+interpro_params:
+  email: your_email@example.com
+  api_timeout: 30
+```
+
+### 2. Run the Search
+
+```bash
+./search_interpro.sh
+```
+
+Or run directly with Python:
+
+```bash
+python3 -m graphgen.run \
+  --config_file examples/search/search_interpro/search_interpro_config.yaml \
+  --output_dir cache/
+```
+
+## Input Format
+
+The input file should be in JSONL format with protein queries:
+
+```jsonl
+{"type": "protein", "content": "P01308"}
+{"type": "protein", "content": "Q96KN2"}
+{"type": "protein", "content": "MHHHHHHSSGVDLGTENLYFQSNAMDFPQQLEACVKQANQALSRFIAPLPFQNTPVVETMQYGALLGGKRLRPFLVYATGHMFGVSTNTLDAPAAAVECIHAYSLIHDDLPAMDDDDLRRGLPTCHVKFGEANAILAGDALQTLAFSILSDANMPEVSDRDRISMISELASASGIAGMCGGQALDLDAEGKHVPLDALERIHRHKTGALIRAAVRLGALSAGDKGRRALPVLDKYAESIGLAFQVQDDILDVVGDTATLGKRQGADQQLGKSTYPALLGLEQARKKARDLIDDARQALKQLAEQSLDTSALEALADYIIQRNK"}
+```
+
+Or in FASTA format:
+```
+>P01308
+MHHHHHHSSGVDLGTENLYFQSNAMDFPQQLEACVKQANQALSRFIAPLPFQNTPVVETMQYGALLGGKRLRPFLVYATGHMFGVSTNTLDAPAAAVECIHAYSLIHDDLPAMDDDDLRRGLPTCHVKFGEANAILAGDALQTLAFSILSDANMPEVSDRDRISMISELASASGIAGMCGGQALDLDAEGKHVPLDALERIHRHKTGALIRAAVRLGALSAGDKGRRALPVLDKYAESIGLAFQVQDDILDVVGDTATLGKRQGADQQLGKSTYPALLGLEQARKKARDLIDDARQALKQLAEQSLDTSALEALADYIIQRNK
+
+>insulin_sequence
+MHHHHHHSSGVDLGTENLYFQS...
+```
+
+
+## Output
+
+The search results will be saved in the output directory with:
+
+```json
+{
+  "molecule_type": "protein",
+  "database": "InterPro",
+  "id": "P01308",
+  "job_id": "iprscan5-R20240123-123456-xxxx-p1m",
+  "content": {
+    "results": [
+      {
+        "xref": [
+          {
+            "ref": "INTERPRO",
+            "id": "IPR000001",
+            "name": "Domain Name"
+          }
+        ],
+        "signature_acc": "PF00001",
+        "go_annotations": [
+          {
+            "id": "GO:0001234",
+            "description": "biological process"
+          }
+        ]
+      }
+    ]
+  },
+  "url": "https://www.ebi.ac.uk/interpro/protein/uniprot/P01308/",
+  "_search_query": "P01308"
+}
+```
+
+## References
+
+- **InterPro Database**: https://www.ebi.ac.uk/interpro/
+- **EBI InterProScan API**: https://www.ebi.ac.uk/Tools/services/rest/iprscan5
+- **UniProt Database**: https://www.uniprot.org/

examples/search/search_protein/search_interpro/search_interpro.sh

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+#!/bin/bash
+# Search InterPro for protein domain annotations
+
+python3 -m graphgen.run \
+  --config_file examples/search/search_protein/search_interpro/search_interpro_config.yaml

examples/search/search_protein/search_interpro/search_interpro_config.yaml

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+global_params:
+  working_dir: cache
+  kv_backend: rocksdb # key-value store backend, support: rocksdb, json_kv
+  graph_backend: kuzu # graph database backend, support: kuzu, networkx
+
+nodes:
+  - id: read_step
+    op_name: read
+    type: source
+    dependencies: []
+    params:
+      input_path:
+        - examples/input_examples/search_interpro_demo.jsonl # input file path, support json, jsonl, txt, pdf. See examples/input_examples for examples
+
+  - id: search_step
+    op_name: search
+    type: map_batch
+    dependencies:
+      - read_step # search_step depends on read_step
+    execution_params:
+      replicas: 1
+      batch_size: 10
+    save_output: true
+    params:
+      data_source: interpro # data source for searcher, support: wikipedia, google, uniprot, ncbi, interpro
+      interpro_params:
+        email: test@example.com # Email address for EBI API requests
+        api_timeout: 30 # Request timeout in seconds

examples/search/search_protein/search_uniprot/search_uniprot.sh

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+python3 -m graphgen.run \
+--config_file examples/search/search_protein/search_uniprot/search_protein_config.yaml

graphgen/models/__init__.py

@@ -42,6 +42,7 @@
         TXTReader,
     )
     from .rephraser import StyleControlledRephraser
+    from .searcher.db.interpro_searcher import InterProSearch
     from .searcher.db.ncbi_searcher import NCBISearch
     from .searcher.db.rnacentral_searcher import RNACentralSearch
     from .searcher.db.uniprot_searcher import UniProtSearch
@@ -95,6 +96,7 @@
     "TXTReader": ".reader",
     "HuggingFaceReader": ".reader",
     # Searcher
+    "InterProSearch": ".searcher.db.interpro_searcher",
     "NCBISearch": ".searcher.db.ncbi_searcher",
     "RNACentralSearch": ".searcher.db.rnacentral_searcher",
     "UniProtSearch": ".searcher.db.uniprot_searcher",