Added unit test for compute_drug_likeness.

atomsci/ddm/test/unit/test_compute_drug_likeness.py

@@ -0,0 +1,44 @@
+import pytest
+import pandas as pd
+from rdkit import Chem
+from atomsci.ddm.utils.rdkit_easy import compute_drug_likeness
+
+def test_compute_drug_likeness():
+    # Create a DataFrame with sample SMILES strings
+    data = {
+        'smiles': [
+            'CCO',  # Ethanol
+            'CC(=O)OC1=CC=CC=C1C(=O)O',  # Aspirin
+            'CC(C)CC1=CC=C(C=C1)C(C)C(=O)O',  # Ibuprofen
+            'C1=CC=C(C=C1)C=O',  # Benzaldehyde
+            'CC(C)NCC(O)COC1=CC=CC=C1'  # Pseudoephedrine
+        ]
+    }
+    df = pd.DataFrame(data)
+    df['mol'] = df['smiles'].apply(Chem.MolFromSmiles)
+
+    # Compute drug likeness
+    result_df = compute_drug_likeness(df, molecule_column='mol')
+
+    # Check if the expected columns are present in the result DataFrame
+    expected_columns = [
+        'MolWt', 'LogP', 'NumHDonors', 'NumHAcceptors', 'TPSA', 'NumRotatableBonds',
+        'MolarRefractivity', 'QED', 'TotalAtoms', 'Lipinski', 'Ghose', 'Veber'
+    ]
+    for col in expected_columns:
+        assert col in result_df.columns
+
+    # Check if the values are computed correctly for a known molecule (Ethanol)
+    ethanol_row = result_df[result_df['smiles'] == 'CCO'].iloc[0]
+    assert pytest.approx(ethanol_row['MolWt'], 0.1) == 46.07
+    assert pytest.approx(ethanol_row['LogP'], 0.1) == -0.0014
+    assert ethanol_row['NumHDonors'] == 1
+    assert ethanol_row['NumHAcceptors'] == 1
+    assert pytest.approx(ethanol_row['TPSA'], 0.1) == 20.23
+    assert ethanol_row['NumRotatableBonds'] == 0
+    assert pytest.approx(ethanol_row['MolarRefractivity'], 0.1) == 12.76
+    assert pytest.approx(ethanol_row['QED'], 0.1) == 0.41
+    assert ethanol_row['TotalAtoms'] == 9
+    assert ethanol_row['Lipinski'] == True
+    assert ethanol_row['Ghose'] == False
+    assert ethanol_row['Veber'] == True