An interview with QuantumLaso

QuantumCure and Annealing Integration

Q: Could you provide a brief introduction to your company and technology?

A: I’ve built QuantumCURE — a quantum-entropy-driven drug discovery platform that integrates classical molecular docking, molecular dynamics, ADME/Tox filtering, and a unique layer of quantum randomness injection.

Unlike traditional deterministic simulations, QuantumCURE uses true quantum entropy from hardware QRNG devices (USB and PCIe) and cloud-based QRNG sources, injecting this entropy at key stages of docking and simulation.

This creates a broader and less biased exploration of chemical space, potentially revealing lead compounds that deterministic methods miss.

My system runs on a fully modular, cloud-native architecture:

• Free, validated core stack: RCSB PDB protein prep, RDKit/meeko ligand prep, AutoDock Vina/QuickVina2 docking, Gnina AI rescoring, OpenMM short MD relaxations, and open-source ADME/Tox prediction.

• Distributed computation: Deployed in Cloud Run containers with GCS storage, and optionally powered by citizen-science volunteers.

• Quantum Entropy Injection: Proprietary entropy harvesting and encoding pipeline stored in GCS and replayed into simulations for reproducibility.

With this approach, QuantumCURE is positioned to identify diverse candidate molecules faster, across a wider range of possibilities, than conventional methods.

Q: How does your platform compare with traditional drug discovery timelines and capabilities?

A: Conventional pipelines often spend years in wet labs running iterative experiments on a narrow slice of chemical space. Even computational approaches can be limited by deterministic search algorithms and bias in their starting conditions.

QuantumCURE compresses the process by:

• Leveraging high-throughput docking and AI rescoring to explore millions of compounds rapidly.

• Running distributed and parallel workloads in the cloud for scalability.

• Using quantum entropy to seed simulations, avoiding repeated patterns that miss novel solutions.

• Providing built-in reproducibility via entropy capture and manifest-driven execution.

The result is faster iteration, broader search, and the ability to “replay” promising runs with exact entropy conditions for verification.

Q: What’s next for QuantumCURE?

A:The next evolution is the Annealing Dimension — integrating a D-Wave quantum annealer into the QuantumCURE portal.

This will allow:

• QUBO-based optimization of docking scores, pharmacophore mappings, and multi-objective hit selection.

• Hybrid quantum-classical workflows where the annealer’s optimization complements our entropy-driven exploration.

• Branding and capability alignment with the very few players in the world using annealing in drug discovery — but with the added differentiator of quantum entropy injection.

The plan is to generate entropy from the D-Wave annealer, store it in GCS alongside QRNG entropy, and make it an optional or blended source in simulations. We’ll also run full optimization problems on D-Wave’s hybrid solver to refine candidate selection.

Q: Who can benefit from working with you right now?

A:

• Pharma & biotech companies seeking differentiated compound libraries and novel leads.

• Academic labs exploring quantum-enhanced computational chemistry.

• Investors looking for early-stage quantum bioinformatics plays with unique IP.

• Strategic partners interested in co-developing quantum-assisted molecular discovery.

We’re already production-ready with the core stack, and the annealing integration will position us alongside — and in some cases ahead of — existing quantum drug discovery players.

So, I have learned about a great product from Polaris. And here is a comparison of my product with theirs. Note that I am a lone developer in Oklahoma, with plenty of time on my hands, exploring quantum computing projects.

Feature / Capability	QuantumCURE (You)	PolarisQB
Core Technology Stack	Modular, cloud-native pipeline with free & validated open-source tools (AutoDock Vina, QuickVina2, Gnina, RDKit, OpenMM, ADMET-AI).	Proprietary docking and screening algorithms integrated with quantum annealing back-end.
Quantum Component	Dual-mode: (1) Quantum entropy injection from hardware QRNGs & cloud QRNG; (2) Quantum annealing optimization via D-Wave hybrid solvers.	Quantum annealing optimization via D-Wave hybrid solvers.
Annealing Use Cases	Planned QUBO mappings for docking score optimization, pharmacophore matching, and multi-objective hit selection; also using annealer as entropy source.	QUBO optimization for chemical space search (claims of 10^23 molecule exploration).
Entropy Strategy	Proprietary entropy harvesting (USB/PCIe QRNGs, ANU cloud QRNG, D-Wave annealer) → stored in GCS → injected into simulations for bias reduction and reproducibility.	No public mention of entropy harvesting or injection; focuses purely on annealing optimization.
Chemical Space Exploration	Millions of compounds now; modular scaling to 100M+ with distributed cloud or volunteer compute; entropy-driven randomization avoids local minima.	Claims to explore up to 10^23 molecules through annealing search algorithms.
Docking Engine	AutoDock Vina (core), QuickVina2 (speed), Gnina (AI rescoring).	Proprietary docking system (details undisclosed).
Protein/Ligand Prep	RCSB PDB → pdbfixer → PDB2PQR/PropKa → ADT (protein); RDKit → meeko → ETKDG → QED/PAINS filter (ligand).	Not disclosed; likely proprietary preprocessing.
Molecular Dynamics	OpenMM minimization / short relax to improve docking pose realism.	Not disclosed.
ADME/Tox Filtering	ADMET-AI or RDKit + XGBoost classifiers for in-silico triage.	Not disclosed.
Deployment Model	Cloud Run containers, GCS storage, citizen-science volunteer compute to distribute workloads.	Commercial SaaS model; no public mention of distributed volunteer computing.
Commercial Positioning	Open-science friendly, upgradeable to licensed tools (OpenEye, Schrödinger) when funded; unique hybrid entropy + annealing story.	Enterprise-focused SaaS, proprietary closed platform, heavy marketing emphasis on annealing “first mover” status.
Differentiator	Only platform combining quantum entropy injection, open modular core, citizen science, and annealing optimization.	First to publicly brand as “annealing-based drug discovery” — but without entropy/crowd layers.

Thank you