⚛️ Version 5.7.5 - Production Ready

Quantum Computing for Drug Discovery

Enterprise-grade quantum platform for molecular docking, binding affinity prediction, ADME/Tox analysis, and CRISPR gene editing optimization. Natural language interface powered by real quantum hardware.

133+

Quantum Qubits

Discovery Modules

Quantum Backends

99.9%

QEC Fidelity

quantum_drug_discovery.py

from bioql import quantum

# Natural language quantum programming
result = quantum(
    "dock aspirin to COX-1 and predict binding affinity",
    backend='ibm_quantum',
    api_key='your_api_key',
    shots=4096
)

# Results with quantum advantage
print(f"Binding Energy: {result.binding_energy} kcal/mol")
print(f"Affinity Kd: {result.affinity_kd} nM")
print(f"Drug-likeness: {result.lipinski_compliant}")

Why Choose BioQL?

The most complete quantum drug discovery platform with proven results

🧬

Natural Language Interface

Write drug discovery workflows in plain English. No quantum gates knowledge required. 164B+ NLP patterns.

✓ Zero quantum programming experience needed
✓ Automatic circuit optimization
✓ Context-aware semantic parsing

⚛️

Real Quantum Hardware

Run on IBM Torino (133 qubits), IonQ trapped ions, Google Cirq, Azure Quantum, and AWS Braket.

✓ Multi-backend support
✓ Automatic error mitigation (ZNE, PEC)
✓ Quantum Error Correction (QEC)

💊

Complete Drug Pipeline

7 production-ready modules: Docking, Binding Affinity, ADME, Toxicity, Pharmacophore, Protein Folding, De Novo Design.

✓ Validated vs. experimental data
✓ 50+ biochemical constants
✓ Real Vina docking integration
✓ Quantum-enhanced molecule generation

🔬

CRISPR-QAI Module

Quantum-enhanced CRISPR guide RNA optimization with off-target prediction and phenotype inference.

✓ Guide sequence encoding
✓ Energy collapse estimation
✓ Multi-backend support

📊

Enterprise Compliance

21 CFR Part 11 aligned provenance logging, cryptographic audit trails, and full reproducibility tracking.

✓ Signed execution records
✓ Compliance dashboards
✓ Export to regulatory formats

⚡

Performance Optimized

Smart caching (24x speedup), job batching (30% cost savings), circuit optimization (35% gate reduction).

✓ <5% profiling overhead
✓ Interactive HTML dashboards
✓ Automatic cost optimization

Drug Discovery Modules

Production-ready quantum algorithms for every stage of drug development

Molecular Docking

Predict ligand-receptor binding poses with quantum advantage

Accuracy ±0.3 kcal/mol

Poses 20+ per run

from bioql.circuits import MolecularDockingCircuit

docking = MolecularDockingCircuit(
    ligand_smiles='CC(=O)OC1=CC=CC=C1C(=O)O',
    receptor_pdb='cox1.pdb',
    num_poses=20
)

result = docking.run_docking(shots=4096)
print(result.best_energy)  # -8.5 kcal/mol

Binding Affinity

VQE-based quantum chemistry for precise Kd/Ki calculation

Range 0.01-100 µM

Parameters ΔG, Kd, Ki, IC50

from bioql.circuits import BindingAffinityCircuit

circuit = BindingAffinityCircuit(
    ligand_smiles="CC(=O)OC1=CC=CC=C1C(=O)O",
    receptor_pdb="protein.pdb",
    n_qubits=12,
    vqe_depth=3
)

result = circuit.estimate_affinity()
print(result.binding_affinity_kd)  # 1.45 nM

ADME Prediction

Quantum ML for pharmacokinetics: Absorption, Distribution, Metabolism, Excretion

Accuracy R² = 0.82

Properties 6+ parameters

from bioql.circuits import ADMECircuit

circuit = ADMECircuit(
    molecule_smiles="CC(=O)OC1=CC=CC=C1C(=O)O"
)

result = circuit.batch_predict()
print(result.bioavailability)  # 65.3%
print(result.half_life)  # 4.2 hours

Toxicity Prediction

Multi-endpoint toxicity screening with quantum classifiers

Endpoints 5 toxicity types

AUC-ROC 0.88 avg

from bioql.circuits import ToxicityPredictionCircuit

circuit = ToxicityPredictionCircuit(
    molecule_smiles="c1ccccc1N(=O)=O"
)

result = circuit.predict_toxicity()
print(result.overall_risk)  # 0.65 (high)
print(result.alerts)  # ['nitro_aromatic']

Pharmacophore Modeling

3D feature extraction for virtual screening and lead optimization

Features 5 types

Conformers 20+ analyzed

from bioql.circuits import PharmacophoreCircuit

circuit = PharmacophoreCircuit(
    molecule_smiles="CC(=O)OC1=CC=CC=C1C(=O)O",
    n_conformers=20
)

model = circuit.generate_pharmacophore()
print(model.features)  # H-bond donors/acceptors...

Protein Folding

QAOA-based optimization for tertiary structure prediction

Algorithm QAOA

Lattice 2D/3D

from bioql.circuits import ProteinFoldingCircuit

folding = ProteinFoldingCircuit()
circuit = folding.build(
    sequence_length=10,
    lattice_dimensions=2,
    qaoa_layers=3
)

result = folding.optimize()
print(result.folding_energy)

De Novo Drug Design

Quantum-enhanced generation of novel drug-like molecules from scratch

Scaffolds 4 types

Validation Lipinski + PAINS

from bioql import quantum

# Design new drug for specific target
result = quantum(
    "design new GLP-1 agonist with high bioavailability",
    backend='ibm_quantum',
    api_key='your_key',
    shots=4096
)

print(result.designed_molecules)  # Novel drug candidates
print(result.best_molecule.smiles)  # Top candidate

Pay-Per-Shot Pricing

Pay only for the quantum shots you execute. No subscriptions, no hidden fees.

💳 Secure Payments via Stripe

All billing managed through Stripe. Usage tracked in real-time. Pay as you go.

Quantum Backend Pricing

Choose your backend and pay per shot executed

Backend	Qubits	Price/Shot	1000 Shots
🖥️ Simulators
IonQ Ideal Simulator	29q	$0.01	$10
AWS SV1 Simulator	34q	$0.01	$10
AWS TN1 Simulator	50q	$0.02	$20
⚛️ Quantum Hardware
IBM Torino	133q	$3.00	$3,000
IBM Brisbane	127q	$3.00	$3,000
IonQ Forte	36q	$3.00	$3,000
IonQ QPU	36q	$2.00	$2,000
QuEra Aquila	256q	$5.00	$5,000

💡 How It Works

You're charged per shot executed based on the quantum backend you choose. Simulators cost $0.01-0.02 per shot, while quantum hardware ranges from $2-5 per shot. All billing is handled securely through Stripe with real-time usage tracking. No minimum commitment required.

Get Started Now

Free tier: 100 shots/month • No credit card required for testing

Quantum Computing for Drug Discovery

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Quantum Computing Meets Drug Discovery

133-Qubit IBM Quantum

Enterprise Quantum Lab

Why Choose BioQL?

Natural Language Interface

Real Quantum Hardware

Complete Drug Pipeline

CRISPR-QAI Module

Enterprise Compliance

Performance Optimized

Drug Discovery Modules

Molecular Docking

Binding Affinity

ADME Prediction

Toxicity Prediction

Pharmacophore Modeling

Protein Folding

De Novo Drug Design

Multi-Backend Quantum Ecosystem

IBM Quantum

IonQ Aria

Google Cirq

Azure Quantum

AWS Braket

Local Simulator

Pay-Per-Shot Pricing

Quantum Backend Pricing

Try BioQL Now