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import pytest
import os
import sys
import logging
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from protac_degradation_predictor import (
get_protac_active_proba,
is_protac_active,
)
import torch
def test_active_proba():
protac_smiles = 'Cc1ncsc1-c1ccc([C@H](C)NC(=O)[C@@H]2C[C@@H](O)CN2C(=O)[C@@H](NC(=O)CC(=O)N2CCN(CC[C@H](CSc3ccccc3)Nc3ccc(S(=O)(=O)NC(=O)c4ccc(N5CCN(CC6=C(c7ccc(Cl)cc7)CCC(C)(C)C6)CC5)cc4)cc3S(=O)(=O)C(F)(F)F)CC2)C(C)(C)C)cc1'
e3_ligase = 'VHL'
target_uniprot = 'Q07817'
cell_line = 'MOLT-4'
device = 'cpu'
active_prob = get_protac_active_proba(
protac_smiles=protac_smiles,
e3_ligase=e3_ligase,
target_uniprot=target_uniprot,
cell_line=cell_line,
device=device,
)
print(f'Active probability: {active_prob} (CPU)')
active_prob = get_protac_active_proba(
protac_smiles=[protac_smiles] * 16,
e3_ligase=[e3_ligase] * 16,
target_uniprot=[target_uniprot] * 16,
cell_line=[cell_line] * 16,
device='gpu' if torch.cuda.is_available() else 'cpu',
)
print(f'Active probability: {active_prob} (GPU)')
def test_is_protac_active():
pass |