Awesome Quantum Drug Discovery

A curated list of resources, papers, software, and tools at the intersection of quantum computing, quantum-inspired methods, and drug discovery.

Please read the contribution guidelines before contributing.

Contents

• Review Papers & Perspectives
• Quantum Chemistry & Molecular Simulation
• Molecular Docking & Virtual Screening
• Protein Folding
• Peptide & Antibody Design
• RNA & Genomics
• Quantum Machine Learning for Drug Discovery
• Drug Combination & Optimization
• Datasets & Benchmarks
• Software & Tools
• Learning Resources
• Quantum Hardware Platforms
• Biochemical Quantum Hardware
• Companies & Startups
• Industry Partnerships & Consortia
• Contributing
• License

Review Papers & Perspectives

Comprehensive reviews and strategic perspectives on quantum computing applications in drug discovery.

Foundational Reviews

• Quantum computing for drug discovery - Early perspective on quantum computing opportunities in pharma. (IEEE, 2018)
• Quantum chemistry in the age of quantum computing - Comprehensive review of quantum algorithms for chemistry. (Chemical Reviews, 2019)
• The prospects of quantum computing in computational molecular biology - Foundational review of quantum computing prospects in molecular biology. (WIREs Comput. Mol. Sci., 2020)

Recent Reviews & Perspectives

• Quantum Computing for Molecular Biology - Road map from ETH Zurich's Quantum for Life Center covering biochemical simulations, structure prediction, and data-driven approaches. (ChemBioChem, 2023)
• A Perspective on Protein Structure Prediction Using Quantum Computers - IBM Quantum perspective on selecting protein structure problems amenable to quantum advantage, with proof-of-concept on Zika Virus NS3 Helicase. (J. Chem. Theory Comput., 2024)
• Quantum biological convergence: quantum computing accelerates KRAS inhibitor design - Commentary on the KRAS breakthrough highlighting QCBMs for navigating chemical space. (Signal Transduction and Targeted Therapy, 2025)
• Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries - Review of QNNs on gate-based quantum computers for property prediction and molecular generation. (Chemical Reviews, 2025)
• Quantum Computing in Drug Discovery: Techniques, Challenges, and Emerging Opportunities - Overview of quantum techniques, current challenges, and emerging opportunities in pharmaceutical applications. (Current Drug Discovery Technologies, 2025)
• Quantum intelligence in drug discovery: Advancing insights with quantum machine learning - Review of QML applications including property prediction, docking simulations, and de novo design. (Drug Discovery Today, 2025)
• Prioritizing quantum computing use cases in the drug discovery and development pipeline - Industry perspective on prioritizing QC applications across the drug development pipeline. (Drug Discovery Today, 2025)
• Quantum-machine-assisted drug discovery - Review examining quantum approaches for molecular simulation, drug-target interaction prediction, and clinical trial optimization. (npj Drug Discovery, 2026)

Industry Perspectives

• BCG Survey - 8 of top 10 biopharma companies piloting quantum projects. (BCG, 2023)
• McKinsey: The quantum revolution in pharma - Strategic overview of quantum opportunities in life sciences. (McKinsey, 2025)

Quantum Chemistry & Molecular Simulation

Quantum approaches for accurate molecular energy calculations, excited-state simulation, and hybrid workflows.

Electronic Structure & Accuracy

• High-Quality Protein Force Fields with Noisy Quantum Processors - Resource estimates and workflow for improving biomolecular force fields via quantum chemistry. (arXiv, 2019)
• Quantum chemical simulations of excited states - Methods for computing excited electronic states relevant to photopharmacology. (arXiv, 2021)
• Reliably assessing the electronic structure of cytochrome P450 on today's classical computers and tomorrow's quantum computers - Boehringer Ingelheim, Google, and QSimulate CYP450 benchmark introducing BLISS+THC for quantum resource reduction. (npj Quantum Information, 2022)
• Drug design on quantum computers - Comprehensive study on quantum methods for drug-relevant molecular simulations. (Nature Physics, 2024)
• Shortcut to chemically accurate quantum computing via density-based basis-set correction - Qubit Pharmaceuticals and Sorbonne University method reducing qubit requirements for molecular simulation. (Nature Communications, 2024)
• Faster Quantum Chemistry Simulations on a Quantum Computer with Improved Tensor Factorization and Active Volume Compilation - PsiQuantum and Boehringer Ingelheim report 234x speedup for CYP450 and 278x for FeMoco using Active Volume compilation. (PRX Quantum, 2025)
• Challenges and Advances in the Simulation of Targeted Covalent Inhibitors Using Quantum Computing - Review of QM/MM scoring functions, warhead reactivity, and quantum computing opportunities for covalent drugs. (J. Phys. Chem. Lett., 2025)

Free Energy, Solvation & Hybrid Pipelines

• Solvent configuration prediction using quantum computing - PASQAL collaboration on protein hydration analysis using neutral-atom quantum computers. (Phys. Rev. Research, 2024)
• A hybrid quantum computing pipeline for real world drug discovery - Practical hybrid quantum-classical pipeline for prodrug activation and covalent bond simulations. (Scientific Reports, 2024)
• Approximate quantum circuit compilation for proton-transfer kinetics on quantum processors - Algorithmiq, AstraZeneca, and Hartree Centre achieve 54% reduction in noisy operations using hardware-adapted fermion-to-qubit mappings. (Phys. Chem. Chem. Phys., 2026)

Molecular Docking & Virtual Screening

Quantum and quantum-inspired approaches for ligand docking, pose prediction, and large-scale screening.

Core Docking Methods

• Molecular docking with Gaussian Boson Sampling - Xanadu/ProteinQure collaboration showing photonic quantum devices can predict docking configurations via maximum weighted clique reductions. (Science Advances, 2020)
• Molecular Docking Using Quantum Mechanical-Based Methods - Review of QM-based docking for improved accuracy. (Methods Mol. Biol., 2020)
• Multibody molecular docking on a quantum annealer - Multibody docking formulation mapped to quantum annealing for biomolecular interaction problems. (arXiv, 2022)
• Molecular docking via quantum approximate optimization algorithm - Pharmacophore-based approach using labeled distance graphs. (arXiv, 2024)
• Quantum molecular docking with quantum-inspired algorithm - QA-inspired binary encodings and hopscotch simulated bifurcation for rugged docking energy landscapes; compared against AutoDock Vina and DiffDock. (arXiv, 2024; JCTC 2024: 10.1021/acs.jctc.4c00141)
• Quantum-Inspired Machine Learning for Molecular Docking - Quantum-inspired optimization combined with diffusion models for blind docking. (arXiv, 2024)
• Quantum Approximate Optimization Algorithms for Molecular Docking - Pfizer-led research mapping docking to maximum vertex weight clique, solved with QAOA and DC-QAOA. (arXiv, 2025)
• Quantum algorithm for protein-ligand docking sites identification - Grover-based algorithm for binding site identification, validated on IBM quantum hardware. (J. Comput. Aided Mol. Des., 2025)

Annealing & Screening Workflows

• Molecular unfolding formulation with enhanced quantum annealing - D-Wave implementation for molecular unfolding in geometric docking, showing 42.5% mean speedup over classical GeoDock. (arXiv, 2024)
• Quantum Algorithm for Structure-Based Virtual Drug Screening Using Classical Force Fields - Uses qubits to evaluate many ligand configurations in superposition while computing binding energies from classical force-field terms. (arXiv, 2025)

Protein Folding

Quantum algorithms and comparative studies for protein and peptide folding.

Lattice, VQE, and Quantum Walk Methods

• A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding - QAOA-style approach splitting optimization into hard and soft constraints. (arXiv, 2018)
• Coarse-grained lattice protein folding on a quantum annealer - Improved Ising-type encodings on D-Wave with record lattice folding of Chignolin and Trp-Cage. (arXiv, 2018)
• Resource-efficient quantum algorithm for protein folding - Introduced CVaR-VQE for tetrahedral-lattice protein folding. (npj Quantum Information, 2021)
• Quantum walks for protein and peptide folding - Quantum-walk-based structure prediction in 3D. (PLOS Comput. Biol., 2021)

Comparative Studies & New Benchmarks

• Quantum synergy in peptide folding: CVaR-VQE vs molecular dynamics - Comparative study of 50 peptides showing CVaR-VQE outperforming MD for global optimization. (Int. J. Biol. Macromol., 2024)
• A comparative insight into peptide folding with quantum CVaR-VQE algorithm - Benchmarks CVaR-VQE against MD and Hidden Markov Models. (Quantum Inf. Process., 2024)
• QuPepFold: A Python package for hybrid quantum-classical protein folding simulations - Modular package targeting intrinsically disordered regions on Qiskit Aer, Amazon Braket, and IonQ Aria-1. (PLOS ONE, 2025)
• Capturing Protein Free Energy Landscape using Efficient Quantum Encoding - FCC lattice encoding with Miyazawa-Jernigan potential, validated on IBM 133-qubit hardware. (arXiv, 2025)
• Quantum-Enabled Protein Folding of Disordered Regions in Ubiquitin C - Error-mitigated VQE for Ubiquitin C terminal region folding. (IEEE, 2025)

Peptide & Antibody Design

Quantum methods specifically targeting biologics discovery.

• Quantum computing for protein design - Approaches for computational protein and peptide engineering.
• Quantum algorithms for antimicrobial peptides - Includes membrane environmental effects without additional qubits.
• De Novo Design of Protein-Binding Peptides by Quantum Computing - Multiscale framework combining D-Wave quantum annealer with classical atomistic docking for peptide design. (J. Chem. Theory Comput., 2025)

RNA & Genomics

Quantum computing applications for RNA structure prediction and genomic analysis.

• Predicting RNA secondary structure using quantum computing - RNA folding formulated as combinatorial optimization on quantum hardware. (bioRxiv, 2021)
• Quantum computing applications in genomics - Survey of quantum approaches for genomic data analysis. (Applied Sciences, 2021)

Quantum Machine Learning for Drug Discovery

Applications of QML to molecule generation, molecular property prediction, and drug-target modeling.

Generative Models & Molecular Design

• Quantum Generative Models for Small Molecule Drug Discovery - Qubit-efficient hybrid quantum GAN generator for learning molecular distributions; includes code. (arXiv, 2021)
• Quantum computing for near-term applications in generative chemistry and drug discovery - Review of NISQ-era quantum applications for de novo molecular generation. (Drug Discovery Today, 2023)
• Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry - Insilico/Zapata/U of T hybrid MolGAN-CQ with quantum discriminator outperforming classical GANs on drug-likeness metrics. (J. Chem. Inf. Model., 2023)
• Hybrid quantum-classical machine learning for generative chemistry and drug design - Hybrid architectures combining quantum circuits with classical networks for molecule generation and property optimization. (Scientific Reports, 2023)
• Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors - First experimentally validated quantum drug discovery study; hybrid QCBM-LSTM screened 1M+ molecules and identified active KRAS binders. (Nature Biotechnology, 2025)
• Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation - Empirical architecture guidelines for hybrid quantum-classical molecular GANs via Bayesian optimization. (arXiv, 2025)
• QCA-MolGAN: Quantum Circuit Associative Molecular GAN with Multi-Agent Reinforcement Learning - QCBM-enabled GAN with multi-agent RL to steer QED/LogP/SA objectives for drug-like molecules. (arXiv, 2025)

Property, Activity, and Interaction Prediction

• Quantum machine learning algorithms for drug discovery applications - Benchmark study using SVM and data reuploading classifier on SARS-CoV-2 and TB datasets. (J. Chem. Inf. Model., 2021)
• Hybrid Quantum Neural Network for Drug Response Prediction - Hybrid QNN for predicting drug response from cell line and chemical inputs. (Cancers, 2023)
• Quantum Machine Learning Predicting ADME-Tox Properties in Drug Discovery - QML models for ADMET property prediction, a key drug discovery bottleneck. (J. Chem. Inf. Model., 2023)
• Robust quantum reservoir computing for molecular property prediction - Quantum reservoir computing for predicting biological activity from molecular descriptors. (arXiv, 2024)
• QKDTI: A quantum kernel based machine learning model for drug target interaction prediction - Quantum-kernel SVR approach evaluated on DAVIS and KIBA, validated on BindingDB. (Scientific Reports, 2025)
• Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery - Quantum multiple-kernel learning for QSAR classification (DYRK1A inhibitors). (arXiv, 2025)

Drug Combination & Optimization

Quantum methods focused on combinatorial treatment strategies and constrained molecular optimization.

• Q-Drug: A Framework to bring Drug Design into Quantum Space - Deep learning combined with quantum annealing for molecular optimization. (arXiv, 2023)
• Towards quantum computing for clinical trial design and optimization - IBM and Cleveland Clinic perspective on quantum optimization for trial site selection and cohort identification. (Trends in Pharmacological Sciences, 2024)
• Network-based prediction of drug combinations with quantum annealing - QUBO formulation using network medicine's complementary exposure principle for combination therapy discovery. (arXiv, 2025)
• Quantum-Aided Drug Design (QuADD) - PolarisQB's D-Wave-based platform for constrained molecular optimization.

Datasets & Benchmarks

Drug Discovery Datasets (Commonly Used in QML)

• BindingDB - Measured binding affinities for protein-ligand interactions; widely used for DTI benchmarks.
• ChEMBL - Open bioactivity database for drug-like molecules and targets.
• MoleculeNet - Benchmark suite of molecular ML datasets commonly used for property prediction. (J. Chem. Inf. Model., 2018)
• Polaris - Registry of benchmark datasets for AI models in drug discovery.
• RCSB Protein Data Bank (PDB) - Structural biology database for protein targets and complexes.
• Therapeutics Data Commons (TDC) - ML-ready datasets and benchmarks spanning targets, molecules, and clinical outcomes. (NeurIPS, 2021)
• ZINC - Database of commercially available compounds for virtual screening.

Quantum/Hybrid Benchmarks & Datasets

• QMugs: Quantum Mechanical Properties of Drug-like Molecules - Large-scale dataset with DFT-calculated properties for drug-like molecules and molecular conformers. (Scientific Data, 2022)
• A performance characterization of quantum generative models - Benchmarking QCBM/QGAN variants useful for selecting architectures in molecular generation pipelines. (arXiv, 2023)
• QDockBank: A Dataset for Ligand Docking on Protein Fragments Predicted on Utility-Level Quantum Computers - Protein-fragment structures for docking benchmarks generated via superconducting quantum processors. (arXiv, 2025)

Software & Tools

Frameworks, SDKs, and practical repositories for quantum drug discovery workflows.

Quantum Chemistry & Simulation

• InQuanto - Quantinuum's quantum computational chemistry platform for molecular simulation workflows.
• OpenFermion - Google's library for compiling and analyzing quantum algorithms for chemistry.
• PennyLane - Xanadu's cross-platform library for differentiable quantum chemistry.
• Qiskit Nature - IBM's quantum chemistry module including ground-state, excited-state, and dipole calculations.
• QURI SDK - QunaSys toolkit for gate-based quantum workflows with chemistry and algorithm modules.
• Tangelo - Quantum chemistry simulation toolkit originally created by Good Chemistry Company, now maintained by SandboxAQ.
• TenCirChem - Tencent's efficient quantum chemistry simulation package built on TensorCircuit.
• TEQUILA - Open-source framework for rapid development of variational quantum algorithms with chemistry applications (Aspuru-Guzik group).

SDKs, Frameworks, and Annealing Toolchains

• Amazon Braket SDK - AWS SDK for quantum computing across multiple hardware backends.
• Cirq - Google's framework for NISQ circuits.
• CUDA-Q - NVIDIA's open-source platform for hybrid quantum-classical application development.
• D-Wave Ocean SDK - Tools for quantum annealing optimization problems.
• dimod - Shared API for Ising and QUBO models.
• Qiskit - IBM's comprehensive quantum computing SDK.
• Qiskit Machine Learning - Qiskit add-on for quantum kernels, QNNs, and hybrid ML workflows.

End-to-End Drug Discovery Repositories

• AWS Quantum Computing Exploration for Drug Discovery - Notebooks for molecular unfolding (QUBO), RNA folding, protein folding (VQE, Grover), and retrosynthetic planning.
• Quantum-ML-Drug-discovery - Tutorial repository demonstrating QML approaches for drug discovery.
• QuPepFold - Python package for CVaR-VQE peptide folding simulations with hardware-agnostic design.

Learning Resources

Educational materials and hands-on tutorials for getting started quickly.

Tutorials & Workshops

• Qiskit Textbook - Quantum Chemistry - VQE for molecular ground states.
• PennyLane Quantum Chemistry Demos - Interactive tutorials on quantum chemistry algorithms.
• AWS Quantum Drug Discovery Workshop - Hands-on notebooks covering molecular unfolding, protein folding, and retrosynthetic planning.
• NVIDIA CUDA-Q: Molecular docking via DC-QAOA - Tutorial implementing DC-QAOA docking (based on arXiv:2308.04098).
• MATLAB Protein Folding VQE Example - Step-by-step VQE implementation for neuropeptide folding.

Quantum Hardware Platforms

Hardware providers with relevance to molecular simulation and drug discovery workflows.

Gate-Based Quantum Computers

• Google Quantum AI - Superconducting processors; partner collaborations include Boehringer Ingelheim.
• IBM Quantum - Superconducting quantum processors; pharma collaborations include Cleveland Clinic (Discovery Accelerator) and Moderna (mRNA design).
• IonQ - Trapped-ion quantum computers available via Amazon Braket and Azure Quantum.
• Quantinuum - H-Series trapped-ion systems with high fidelity; Microsoft partnership demonstrated 12 logical qubits for chemistry (2024).
• Rigetti - Superconducting quantum processors available via Rigetti QCS and Amazon Braket.

Photonic Quantum Computers

• PsiQuantum - Photonic quantum computing; pharma collaborations include Boehringer Ingelheim (CYP450 simulation).
• Xanadu - Photonic quantum computing; creators of PennyLane and Strawberry Fields, with applications including Gaussian Boson Sampling.

Quantum Annealers

• D-Wave - 5000+ qubit annealing systems used in molecular docking and constrained optimization.

Neutral-Atom Quantum Computers

• PASQAL - Neutral-atom processors; partner collaborations include Qubit Pharmaceuticals.
• QuEra Computing - Neutral-atom systems with collaborations including Merck KGaA and Amgen.

Biochemical Quantum Hardware

Biomolecular systems as quantum computing platforms.

• Peptides as Versatile Platforms for Quantum Computing - Lanthanide-binding peptide tags as molecular qubits demonstrating coherent oscillations via pulsed EPR. (J. Phys. Chem. Lett., 2018)

Companies & Startups

Organizations building products and services at the intersection of quantum computing and drug discovery.

Quantum-Native Drug Discovery & Platform Companies

• Algorithmiq (Finland) - Aurora platform with IBM partnership, quantum network medicine focus, and Cleveland Clinic cancer drug collaboration.
• Aqemia (France) - Quantum-inspired statistical mechanics for affinity prediction.
• Kuano (UK) - Quantum machine learning for molecular discovery.
• Menten AI (USA/Canada) - Quantum-enhanced peptide and protein design.
• Phasecraft (UK) - Quantum algorithms for drug discovery; Wellcome Leap Q4Bio covalent inhibitor project with University of Nottingham and QuEra.
• Polaris Quantum Biotech (PolarisQB) (USA) - QuADD platform on D-Wave for lead identification and constrained molecular optimization.
• ProteinQure (Canada) - Peptide drug discovery with long-term quantum R&D focus.
• QC Ware (USA) - Promethium quantum chemistry SaaS platform; partnerships include Merck KGaA and NVIDIA Quantum Cloud integration.
• QSimulate (USA) - Ab initio quantum simulation for drug discovery.
• Qubit Pharmaceuticals (France/USA) - Atlas platform combining HPC simulation with quantum algorithms; WEF Technology Pioneer 2024.
• SandboxAQ (USA) - Developer of Tangelo and AQChemSim (formerly QEMIST Cloud); collaborations include AstraZeneca and Sanofi.
• XtalPi (China/USA) - ID4 platform combining quantum mechanics and AI; partnerships include Pfizer.

Quantum Software Providers with Pharma Engagement

• 1QBit (Canada) - Quantum software provider; pharma partnership history includes Biogen (via Accenture).
• HQS Quantum Simulations (Germany) - Quantum chemistry software; three-year partnership with Merck KGaA for drug screening and molecular property prediction.
• QunaSys (Japan) - Quantum chemistry software company and lead coordinator of the QuEnAIS quantum-AI drug discovery consortium.

Industry Partnerships & Consortia

Collaborative initiatives advancing quantum drug discovery.

• IBM Quantum Network - Includes Cleveland Clinic (Discovery Accelerator), Moderna, and multiple pharma partners.
• QIDO - Quantum-Integrated Discovery Orchestrator platform by Mitsui, QSimulate, and Quantinuum for drug and materials discovery; beta tested by Chugai Pharmaceutical (2025).
• QuEnAIS - Quantum-AI drug discovery consortium led by QunaSys.
• QuPharm - Alliance of pharmaceutical companies developing quantum computing solutions for drug discovery.
• SEEQC Consortium - UK-led project with Oxford University and Merck KGaA to build full-stack quantum systems for pharma applications.
• Wellcome Leap Q4Bio - Program supporting quantum-enabled biological and pharmaceutical research; Phase 3 projects (2025) include Phasecraft/QuEra covalent inhibitor work.

Funding Commitments

• Novo Holdings - DKK 1.4 billion (~€188M) commitment to quantum computing in life sciences, with portfolio including Phasecraft and Sparrow Quantum (2024).

Pharma Companies with Quantum Programs

• Amgen - QuEra collaboration for molecular property prediction.
• AstraZeneca - SandboxAQ and Riverlane partnerships.
• Biogen - 1QBit/Accenture quantum molecular comparison validation.
• Boehringer Ingelheim - Collaborations with Google Quantum AI and PsiQuantum (CYP450 simulation); studies including quantum chemistry for metalloenzymes.
• Johnson & Johnson - Patent filings and quantum research programs.
• Merck KGaA - Multiple initiatives including SEEQC consortium, QC Ware partnership, and QuEra collaboration.
• Moderna - IBM collaboration for mRNA medicine design.
• Pfizer - Quantum algorithm development for molecular docking and simulation.
• Roche - Internal quantum research programs and startup collaborations.
• Sanofi - SandboxAQ partnership for molecular simulation and AI-driven biomarker identification in clinical development (2024).

Contributing

Contributions welcome! Please read our contribution guidelines first.

When adding new resources:

• Include publication year and source
• Provide brief description of the quantum method used
• Link to papers, code repositories, or official documentation
• Verify links are accessible

License

To the extent possible under law, the contributors have waived all copyright and related or neighboring rights to this work.

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Curated by Mark Fingerhuth, passionate about the intersection of quantum computing and drug discovery. For the latest in open-source quantum software more broadly, see Awesome Quantum Software.