QuantumCURE Pro™
QuantumCURE Pro™ Entangler
Fall 2026
Introduction
QuantumCURE Pro™ Entangler exists because a specific set of hard problems were solved—quietly, methodically, and over time. Over a two-year development cycle, QuantumLaso focused on three core capabilities that rarely coexist in a single system and are almost never available in a private, turnkey form:
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Full cloud orchestration of legacy Vina docking, modernized for scalable, repeatable, and auditable operation across millions of compounds.
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Live quantum entropy harvesting, sourced from real QRNG hardware, continuously injected into molecular exploration rather than simulated or approximated.
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Symbolic Zaban glyph assignment, preserving collapse-path context and discovery signatures that cannot be captured by numerical scores alone.
Each of these components is individually non-trivial. Together, they form the foundation of a new class of molecular discovery instrument. The result is not a web service, not a black-box AI, and not a competitor to Schrödinger or Atomwise. Entangler is a private molecular forging engine—designed for research teams that want to own their data, control their entropy sources, and operate discovery pipelines inside secure or IP-sensitive environments.
By separating orchestration (cloud) from decision-making (local), and combining deterministic computation with quantum-seeded exploration, Entangler enables cancer drug discovery workflows that are:
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Reproducible, yet non-degenerate
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Scalable, yet sovereign
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Classical in execution, yet quantum-enhanced in exploration
This system was built to serve startups, serious labs, and stealth research groups that value independence over convenience and instrumentation over platforms. QuantumCURE Pro™ Entangler is the physical embodiment of that philosophy, a turnkey instrument made possible only after years of foundational work in cloud docking, entropy engineering, and symbolic analysis.
The Product
QuantumCURE Pro™ Entangler (Atlas Edition) is a sovereign, on-premise molecular discovery instrument designed for cancer drug research teams that require privacy, reproducibility, and full control over their discovery pipeline.
At its core, Entangler unifies three hard-to-replicate capabilities into a single system:
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Cloud-orchestrated Vina docking at scale, enabling systematic screening of millions of compounds across multiple protein targets.
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Live quantum entropy harvesting via PCIe or USB QRNG hardware, injecting real physical randomness into molecular exploration and collapse-path discovery.
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Symbolic Zaban glyph assignment, capturing non-numerical collapse signatures that preserve discovery context beyond raw scores.
The system continuously forges and refines a local Wet List—a curated, target-specific shortlist of high-value molecular candidates—ready for downstream molecular dynamics, IC₅₀ modeling, and AI-based inference.
Entangler is not a SaaS dependency, not a black-box model, and not a Schrödinger replacement.
It is a private molecular forging instrument, designed for labs that want to own both their data and their discovery process.
🧱 Founders Edition — Atlas Hardware Specifications (Prototype)
Chassis Class: Dual-socket workstation / tower
Operating System: Windows 11 Pro for Workstations
Deployment Model: On-premise with cloud burst orchestration
Compute
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Dual-socket CPU architecture (AMD EPYC or Intel Xeon class)
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64–192 physical CPU cores (configurable)
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Optimized for high-throughput, embarrassingly parallel workloads
Memory & Storage
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128–512 GB ECC RAM
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High-speed NVMe scratch storage (local docking, prep, caching)
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Dedicated storage partition for Wet List and audit logs
Quantum Entropy
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PCIe QRNG (preferred) or USB QRNG support
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Continuous entropy harvesting daemon
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Entropy provenance logging (source, hash, timestamp)
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PRNG fallback with explicit mode tagging
Acceleration (Optional Add-Ons)
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NVIDIA GPU(s) for:
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GNN / GANN inference
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SKALA models
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AI rescoring and clustering
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CUDA-enabled, but not required for core docking
Networking
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Secure outbound cloud connectivity
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No inbound dependencies required
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Compatible with air-gapped / restricted environments (cloud optional)
🔥 The Forge Pipeline (Operational Core)
Entangler runs the Forge Pipeline, a deterministic-yet-entropy-aware workflow:
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Ligand preparation (cached, reproducible)
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Target-specific docking orchestration (local + cloud)
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Score aggregation and pose analysis
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Zaban glyph assignment (symbolic collapse tagging)
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Wet List promotion based on score, diversity, and symbolic signatures
Only compounds that survive the Forge are promoted to:
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Molecular Dynamics
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IC₅₀ modeling
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AI / SKALA inference
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Experimental handoff
This dramatically reduces downstream cost and noise.
🪪 Founders Edition
QuantumCURE Pro™ Entangler, Atlas Edition — Founders Series
A private molecular entanglement engine for cancer drug discovery.
Forged with quantum entropy.
Orchestrated through the cloud.
Curated by symbolic collapse.
Built by QuantumLaso, LLC
2026 Prototype Series
🗺️ 2026 Prototype Roadmap
Q1–Q2 2026 — Core Stabilization
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Finalize cloud Vina orchestration (multi-target, shard-based)
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Harden entropy daemon (PCIe + USB QRNG)
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Standardize run manifests, Wet List schema, and audit logs
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CLI-first operation (batch + daemon driven)
Q2–Q3 2026 — Local Atlas Integration
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Hardware BOM selection and validation
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NUMA-aware job scheduling
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Local Wet List persistence and replay
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PRNG vs QRNG paired-run comparison tooling
Q3 2026 — Symbolic & AI Expansion
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Zaban glyph stabilization and export formats
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Initial AI rescoring / clustering hooks
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SKALA integration (Founders preview)
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GPU acceleration validation (optional)
Q4 2026 — Founders Edition Prototype
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First complete Atlas box assembled
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Internal validation on real cancer targets
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End-to-end demo: entropy → dock → glyph → Wet List
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Founder-level documentation and onboarding
🎯 Positioning
QuantumCURE Pro™ Entangler is not a docking tool. It is a private molecular forging instrument—designed to entangle quantum entropy, classical computation, and symbolic intelligence into actionable cancer drug candidates.
Local processing time estimation:
So, with 64–192 physical cores and 512 GB RAM, the local side (prep + packaging + result parsing + Wet List writes) can be very fast. But since Vina is on the cloud, your end-to-end wall time will usually be:
Total time ≈ max(Local prep + post, Cloud docking throughput)
So below I’m providing realistic local-time ranges (prep + submit + parse/write), and you can compare them to whatever your cloud throughput is. I will benchmark the process as development progresses and will post in this space.
Assumptions (realistic, not “best case”)
Two local prep modes:
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Fast / cached prep: ligands already standardized, minimal 3D work (or conformers cached).
~0.4 CPU-seconds per compound total local work. -
Full prep: SMILES → 3D conformers + protonation/charges + PDBQT generation + bookkeeping.
~3.0 CPU-seconds per compound total local work.
Parallel efficiency assumptions (overhead + I/O + Python/RDKit realities):
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64-core workstation → ~50 effective cores
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192-core workstation → ~150 effective cores
Local processing time (prep + submit + parse/write)
Compounds64-core WS (Fast / Cached)64-core WS (Full Prep)192-core WS (Fast / Cached)192-core
What this table is telling you
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With 192 cores, you can prep 1,000,000 compounds locally in ~44 minutes (cached) to ~5.6 hours (full prep).
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With 64 cores, the same job is ~2.2 hours (cached) to ~16.7 hours (full prep).
The cloud docking check (so you don’t mis-estimate)
Because docking is cloud-side, if your cloud fleet can do (for example):
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100 ligands/second total, then 1,000,000 ligands ≈ 2.8 hours docking time
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500 ligands/second total, then 1,000,000 ligands ≈ 0.56 hours (~34 minutes)
So depending on your cloud throughput:
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Your local box may be the bottleneck (if cloud is huge), or
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Your cloud may be the bottleneck (if cloud is small)

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