better handling if mkdssp is not installed

Author: lucidrains

alphafold3_pytorch/alphafold3.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import sh
 from math import pi, sqrt
 from pathlib import Path
 from itertools import product
@@ -4083,6 +4084,14 @@ def __init__(
 
         self.dssp_path = dssp_path
 
+    @property
+    def can_calculate_unresolved_protein_rasa(self):
+        try:
+            sh.which('mkdssp')
+            return True
+        except:
+            return False
+
     @typecheck
     def compute_gpde(
         self,
@@ -4314,6 +4323,8 @@ def _compute_unresolved_rasa(
         atom_mask: True for valid atom, False for missing/padding atom
         """
 
+        assert self.can_calculate_unresolved_protein_rasa, 'mkdssp needs to be installed'
+
         residue_constants = get_residue_constants(res_chem_index=IS_PROTEIN)
 
         device = atom_pos.device

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "alphafold3-pytorch"
-version = "0.2.100"
+version = "0.2.101"
 description = "Alphafold 3 - Pytorch"
 authors = [
     { name = "Phil Wang", email = "[email protected]" }
@@ -45,6 +45,7 @@ dependencies = [
     "pyyaml",
     "rdkit>=2023.9.6",
     "scikit-learn>=1.5.0",
+    "sh>=2.0.7",
     "shortuuid",
     "taylor-series-linear-attention>=0.1.9",
     "timeout_decorator>=0.5.0",

tests/test_af3.py

@@ -1106,13 +1106,6 @@ def test_model_selection_score():
 
 def test_unresolved_protein_rasa():
 
-    # skip the test if dssp not installed
-
-    try:
-        subprocess.check_output(["which", "mkdssp"])
-    except:
-        pytest.skip("mkdssp not found, test_unresolved_protein_rasa skipped")
-
     # rest of the test
 
     mmcif_filepath = os.path.join('data', 'test', '7a4d-assembly1.cif')
@@ -1138,6 +1131,9 @@ def test_unresolved_protein_rasa():
 
     compute_model_selection_score = ComputeModelSelectionScore()
 
+    if not compute_model_selection_score.can_calculate_unresolved_protein_rasa:
+        pytest.skip("mkdssp not available for calculating unresolved protein rasa")
+
     unresolved_rasa = compute_model_selection_score.compute_unresolved_rasa(
         unresolved_cid=[1],
         unresolved_residue_mask=unresolved_residue_mask,