API Reference

Core Functions

quantum(program, backend, api_key, shots)

Main entry point for quantum computations with natural language interface.

from bioql import quantum

result = quantum(
    program="dock aspirin to COX-1",
    backend='simulator',
    api_key='your_key',
    shots=4096
)

run_complete_pipeline(molecule_smiles, target_protein_pdb)

Execute complete drug discovery pipeline: docking, affinity, ADME, toxicity.

from bioql import run_complete_pipeline

results = run_complete_pipeline(
    molecule_smiles="CC(=O)OC1=CC=CC=C1C(=O)O",
    target_protein_pdb="cox1.pdb",
    backend='ibm_quantum'
)

Module Classes

MolecularDockingCircuit

Quantum molecular docking with VQE algorithm.

Methods: run_docking(), get_poses(), calculate_affinity()

ADMECircuit

Quantum ML for pharmacokinetics prediction.

Methods: batch_predict(), predict_absorption(), calculate_bioavailability()

ToxicityPredictionCircuit

Multi-endpoint toxicity screening with quantum classifiers.

Methods: predict_toxicity(), get_alerts(), calculate_risk_score()

Quantum Backends

BioQL supports multiple quantum computing platforms for running your drug discovery workflows.

IBM Quantum

backend='ibm_quantum'

Access to IBM's quantum computers with up to 127 qubits

IonQ

backend='ionq'

Trapped-ion quantum computers with high fidelity

Azure Quantum

backend='azure_quantum'

Microsoft's cloud-based quantum computing service

AWS Braket

backend='aws_braket'

Amazon's quantum computing service with multiple providers

Backend Usage Example

from bioql import quantum

# Run on IBM Quantum
result = quantum(
    program="dock aspirin to COX-1",
    backend='ibm_quantum',
    api_key='your_ibm_key',
    shots=4096
)

# Run on IonQ
result = quantum(
    program="dock aspirin to COX-1",
    backend='ionq',
    api_key='your_ionq_key',
    shots=4096
)

# Or use the fast simulator for development
result = quantum(
    program="dock aspirin to COX-1",
    backend='simulator',
    shots=1024
)

← Back to Documentation