Upload scripts/download_alphafold_structures.py with huggingface_hub

scripts/download_alphafold_structures.py

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+#!/usr/bin/env python3
+"""
+Download AlphaFold structures from AlphaFold Database.
+Part of APED - African Protein Engineering Dataset
+"""
+
+import argparse
+import os
+import time
+import requests
+from pathlib import Path
+
+
+ALPHAFOLD_DB_URL = "https://alphafold.ebi.ac.uk/files/AF-{uniprot_id}-F1-model_v4.pdb"
+UNIPROT_API_URL = "https://rest.uniprot.org/uniprotkb/search"
+
+
+def get_uniprot_ids_by_taxonomy(taxonomy_ids: list, limit: int = 500) -> list:
+    """Fetch UniProt IDs for given taxonomy IDs."""
+    all_ids = []
+    
+    for tax_id in taxonomy_ids:
+        print(f"Fetching proteins for taxonomy ID: {tax_id}")
+        
+        query = f"(taxonomy_id:{tax_id}) AND (reviewed:true)"
+        params = {
+            "query": query,
+            "format": "list",
+            "size": limit
+        }
+        
+        try:
+            response = requests.get(UNIPROT_API_URL, params=params, timeout=30)
+            response.raise_for_status()
+            ids = response.text.strip().split('\n')
+            ids = [i for i in ids if i]
+            all_ids.extend(ids)
+            print(f"  Found {len(ids)} proteins")
+        except requests.RequestException as e:
+            print(f"  Error fetching taxonomy {tax_id}: {e}")
+        
+        time.sleep(0.5)  # Rate limiting
+    
+    return list(set(all_ids))
+
+
+def download_alphafold_structure(uniprot_id: str, output_dir: Path) -> bool:
+    """Download a single AlphaFold structure."""
+    output_file = output_dir / f"AF-{uniprot_id}-F1-model_v4.pdb"
+    
+    if output_file.exists():
+        return True
+    
+    url = ALPHAFOLD_DB_URL.format(uniprot_id=uniprot_id)
+    
+    try:
+        response = requests.get(url, timeout=30)
+        response.raise_for_status()
+        
+        with open(output_file, 'w') as f:
+            f.write(response.text)
+        return True
+        
+    except requests.RequestException:
+        return False
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Download AlphaFold structures for thermophilic organisms"
+    )
+    parser.add_argument(
+        "--taxonomy-ids",
+        type=str,
+        required=True,
+        help="Comma-separated taxonomy IDs (e.g., 274,69014,2287)"
+    )
+    parser.add_argument(
+        "--output-dir",
+        type=str,
+        default="data/structures/alphafold_db/",
+        help="Output directory for PDB files"
+    )
+    parser.add_argument(
+        "--limit",
+        type=int,
+        default=500,
+        help="Max proteins per organism"
+    )
+    parser.add_argument(
+        "--uniprot-ids-file",
+        type=str,
+        help="Optional: File with UniProt IDs (one per line)"
+    )
+    
+    args = parser.parse_args()
+    
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+    
+    # Get UniProt IDs
+    if args.uniprot_ids_file:
+        with open(args.uniprot_ids_file) as f:
+            uniprot_ids = [line.strip() for line in f if line.strip()]
+    else:
+        taxonomy_ids = [int(t.strip()) for t in args.taxonomy_ids.split(',')]
+        uniprot_ids = get_uniprot_ids_by_taxonomy(taxonomy_ids, args.limit)
+    
+    print(f"\nDownloading {len(uniprot_ids)} structures...")
+    
+    success = 0
+    failed = 0
+    
+    for i, uid in enumerate(uniprot_ids):
+        if download_alphafold_structure(uid, output_dir):
+            success += 1
+        else:
+            failed += 1
+        
+        if (i + 1) % 50 == 0:
+            print(f"  Progress: {i + 1}/{len(uniprot_ids)} (success: {success}, failed: {failed})")
+        
+        time.sleep(0.1)  # Rate limiting
+    
+    print(f"\nComplete!")
+    print(f"  Downloaded: {success}")
+    print(f"  Failed: {failed}")
+    print(f"  Output: {output_dir}")
+
+
+if __name__ == "__main__":
+    main()