#!/usr/bin/env python3"""ChEMBL Database Query Examples This script demonstrates common query patterns for the ChEMBL databaseusing the chembl_webresource_client Python library. Requirements:    pip install chembl_webresource_client    pip install pandas (optional, for data manipulation)""" from chembl_webresource_client.new_client import new_client  def get_molecule_info(chembl_id):    """    Retrieve detailed information about a molecule by ChEMBL ID.     Args:        chembl_id: ChEMBL identifier (e.g., 'CHEMBL25')     Returns:        Dictionary containing molecule information    """    molecule = new_client.molecule    return molecule.get(chembl_id)  def search_molecules_by_name(name_pattern):    """    Search for molecules by name pattern.     Args:        name_pattern: Name or pattern to search for     Returns:        List of matching molecules    """    molecule = new_client.molecule    results = molecule.filter(pref_name__icontains=name_pattern)    return list(results)  def find_molecules_by_properties(max_mw=500, min_logp=None, max_logp=None):    """    Find molecules based on physicochemical properties.     Args:        max_mw: Maximum molecular weight        min_logp: Minimum LogP value        max_logp: Maximum LogP value     Returns:        List of matching molecules    """    molecule = new_client.molecule     filters = {        'molecule_properties__mw_freebase__lte': max_mw    }     if min_logp is not None:        filters['molecule_properties__alogp__gte'] = min_logp    if max_logp is not None:        filters['molecule_properties__alogp__lte'] = max_logp     results = molecule.filter(**filters)    return list(results)  def get_target_info(target_chembl_id):    """    Retrieve information about a biological target.     Args:        target_chembl_id: ChEMBL target identifier (e.g., 'CHEMBL240')     Returns:        Dictionary containing target information    """    target = new_client.target    return target.get(target_chembl_id)  def search_targets_by_name(target_name):    """    Search for targets by name or keyword.     Args:        target_name: Target name or keyword (e.g., 'kinase', 'EGFR')     Returns:        List of matching targets    """    target = new_client.target    results = target.filter(        target_type='SINGLE PROTEIN',        pref_name__icontains=target_name    )    return list(results)  def get_bioactivity_data(target_chembl_id, activity_type='IC50', max_value=100):    """    Retrieve bioactivity data for a specific target.     Args:        target_chembl_id: ChEMBL target identifier        activity_type: Type of activity (IC50, Ki, EC50, etc.)        max_value: Maximum activity value in nM     Returns:        List of activity records    """    activity = new_client.activity    results = activity.filter(        target_chembl_id=target_chembl_id,        standard_type=activity_type,        standard_value__lte=max_value,        standard_units='nM'    )    return list(results)  def find_similar_compounds(smiles, similarity_threshold=85):    """    Find compounds similar to a query structure.     Args:        smiles: SMILES string of query molecule        similarity_threshold: Minimum similarity percentage (0-100)     Returns:        List of similar compounds    """    similarity = new_client.similarity    results = similarity.filter(        smiles=smiles,        similarity=similarity_threshold    )    return list(results)  def substructure_search(smiles):    """    Search for compounds containing a specific substructure.     Args:        smiles: SMILES string of substructure     Returns:        List of compounds containing the substructure    """    substructure = new_client.substructure    results = substructure.filter(smiles=smiles)    return list(results)  def get_drug_info(molecule_chembl_id):    """    Retrieve drug information including indications and mechanisms.     Args:        molecule_chembl_id: ChEMBL molecule identifier     Returns:        Tuple of (drug_info, mechanisms, indications)    """    drug = new_client.drug    mechanism = new_client.mechanism    drug_indication = new_client.drug_indication     try:        drug_info = drug.get(molecule_chembl_id)    except:        drug_info = None     mechanisms = list(mechanism.filter(molecule_chembl_id=molecule_chembl_id))    indications = list(drug_indication.filter(molecule_chembl_id=molecule_chembl_id))     return drug_info, mechanisms, indications  def find_kinase_inhibitors(max_ic50=100):    """    Find potent kinase inhibitors.     Args:        max_ic50: Maximum IC50 value in nM     Returns:        List of kinase inhibitor activities    """    target = new_client.target    activity = new_client.activity     # Find kinase targets    kinase_targets = target.filter(        target_type='SINGLE PROTEIN',        pref_name__icontains='kinase'    )     # Get target IDs    target_ids = [t['target_chembl_id'] for t in kinase_targets[:10]]  # Limit to first 10     # Find activities    results = activity.filter(        target_chembl_id__in=target_ids,        standard_type='IC50',        standard_value__lte=max_ic50,        standard_units='nM'    )     return list(results)  def get_compound_bioactivities(molecule_chembl_id):    """    Get all bioactivity data for a specific compound.     Args:        molecule_chembl_id: ChEMBL molecule identifier     Returns:        List of all activity records for the compound    """    activity = new_client.activity    results = activity.filter(        molecule_chembl_id=molecule_chembl_id,        pchembl_value__isnull=False    )    return list(results)  def export_to_dataframe(data):    """    Convert ChEMBL data to pandas DataFrame (requires pandas).     Args:        data: List of ChEMBL records     Returns:        pandas DataFrame    """    try:        import pandas as pd        return pd.DataFrame(data)    except ImportError:        print("pandas not installed. Install with: pip install pandas")        return None  # Example usageif __name__ == "__main__":    print("ChEMBL Database Query Examples")    print("=" * 50)     # Example 1: Get information about aspirin    print("\n1. Getting information about aspirin (CHEMBL25)...")    aspirin = get_molecule_info('CHEMBL25')    print(f"Name: {aspirin.get('pref_name')}")    print(f"Formula: {aspirin.get('molecule_properties', {}).get('full_molformula')}")     # Example 2: Search for EGFR inhibitors    print("\n2. Searching for EGFR targets...")    egfr_targets = search_targets_by_name('EGFR')    if egfr_targets:        print(f"Found {len(egfr_targets)} EGFR-related targets")        print(f"First target: {egfr_targets[0]['pref_name']}")     # Example 3: Find potent activities for a target    print("\n3. Finding potent compounds for EGFR (CHEMBL203)...")    activities = get_bioactivity_data('CHEMBL203', 'IC50', max_value=10)    print(f"Found {len(activities)} compounds with IC50 <= 10 nM")     print("\n" + "=" * 50)    print("Examples completed successfully!")