| from modrag_protein_functions import uniprot_node, listbioactives_node, getbioactives_node, predict_node, docking_node
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| from modrag_molecule_functions import smiles_node
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|
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| def get_actives_for_protein(query_protein: str):
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| '''
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| Finds Bioactive molecules for a give protein. Uses Uniprot to find chembl IDs for the
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| protein, and then queries chembl for bioative molecules.
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| Args:
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| query_protein: The protein to search for.
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| Returns:
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| bioactives_for_protein_string: A string containing bioactive molecules.
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| bioacts_images: A list of images of the bioactives.
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| '''
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| bioactives_for_protein_string = ''
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| up_ac_list, ids_string, _ = uniprot_node([query_protein])
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| bioactives_for_protein_string += 'Found the following Uniprot ACs: \n'
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| for up_ac in up_ac_list[0]:
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| bioactives_for_protein_string += up_ac + ', \n'
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| bioacts, chembl_string, chembl_ids = listbioactives_node(up_ac_list[0])
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| bioactives_for_protein_string += 'Found the following chembl IDs: \n'
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| largest = 0
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| for bioact_num, chemblid in zip(bioacts[0], chembl_ids[0]):
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| bioactives_for_protein_string += f'{chemblid}: {bioact_num} bioactive molecules. \n'
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| if bioact_num > largest:
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| largest = bioact_num
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| largest_id = chemblid
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| if largest == 0:
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| return 'No bioactives found for protein', None
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|
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| bioactives_for_protein_string += f'Chose the Chembl ID {largest_id} with {largest} bioactive molecules. \n'
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| bioacts, bioacts_string, bioacts_images = getbioactives_node([largest_id])
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| bioactives_for_protein_string += bioacts_string
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| return bioacts, bioactives_for_protein_string, bioacts_images
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|
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| def get_predictions_for_protein(smiles_list: list[str], query_protein: str):
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| '''
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|
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| Uses Uniprot to find chembl IDs for the protein, and then queries chembl for
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| bioactive molecules to train a model and predict the activity of the given smiles.
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| Args:
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| smiles_list: A list of SMILES strings.
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| query_protein: The protein to search for.
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| Returns:
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| bioactives_for_protein_string: A string containing bioactive molecules.
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| bioacts_images: A list of images of the bioactives.
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| '''
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| predictions_string = ''
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| up_ac_list, ids_string, _ = uniprot_node([query_protein])
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| predictions_string += 'Found the following Uniprot ACs: \n'
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| for up_ac in up_ac_list[0]:
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| predictions_string += up_ac + ', \n'
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| bioacts, chembl_string, chembl_ids = listbioactives_node(up_ac_list[0])
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| predictions_string += 'Found the following chembl IDs: \n'
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| largest = 0
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| for bioact_num, chemblid in zip(bioacts[0], chembl_ids[0]):
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| predictions_string += f'{chemblid}: {bioact_num} bioactive molecules. \n'
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| if bioact_num > largest:
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| largest = bioact_num
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| largest_id = chemblid
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| if largest == 0:
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| return [], 'No bioactives found for protein'
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| predictions_string += f'Chose the Chembl ID {largest_id} with {largest} bioactive molecules. \n'
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| preds, preds_string, _ = predict_node(smiles_list, largest_id)
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| predictions_string += preds_string
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| return preds, predictions_string, None
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|
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| def dock_from_names(names_list: list[str], protein: str):
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| '''
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| Accepts names of molecules and docks them in a given protein.
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| Args:
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| names_list: A list of names of molecules.
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| protein: The protein to dock in.
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| Returns:
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| dock_from_names_string: A string containing the docking scores for the molecules.
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| '''
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| dock_from_names_string = ''
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| smiles_list, smiles_string, _ = smiles_node(names_list)
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| for smiles, names in zip(smiles_list, names_list):
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| dock_from_names_string += f'The SMILES for {names} is {smiles}. \n'
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| scores, scores_string, _ = docking_node(smiles_list, protein)
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| for score, name in zip(scores, names_list):
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| dock_from_names_string += f'The docking score for {name} is {score}. \n'
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| return scores, dock_from_names_string, None
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| |
