I Just Pulled an EGFR Golden List Out of the Quantum Vacuum
- mansour ansari
- Dec 2, 2025
- 5 min read
Updated: Dec 7, 2025
QuantumCURE Pro ™ screen shots -
Round two of QuantumCURE pro™ software validation is officially in the books.
Some people pick up fishing or golf in retirement. I enjoy those too, but for the last few years I’ve been teaching myself quantum computing, cheminformatics, and how to build full cancer drug discovery portals. Why? People ask me that a lot. My answer is simple: why not? I want to be useful, and I still have work to do.
I sit in a cold Oklahoma garage, lift heavy weights as a hobby, wire a hardware QRNG into a molecular docking engine… and tonight that thing spit out one of the nastiest EGFR hit lists I’ve ever seen.
This wasn’t a toy demo. This was a full QuantumCURE Pro™ run against EGFR, seeded with true quantum entropy and fingerprinted with my CRISP-G glyph system.
The result:👉 11 pharma-grade candidates in one shot.
Let me show you why this matters.
1. Binding Affinity: Deep in the Big-Leagues
The top of the list looks like this:
Best affinity: −11.96 kcal/mol
Band for the whole set: roughly −10.6 to −11.9 kcal/mol
For context:
Many “good” virtual hits sit around −7 to −9 kcal/mol
Below −10 kcal/mol you’re entering serious lead territory
Pushing ~−12 kcal/mol is the same neighborhood where best-in-class kinase inhibitors like Imatinib live on paper
So I didn’t just get one lucky outlier. I got an entire row of monsters all packed into that high-affinity band.
2. Predicted IC50: Sub-Nanomolar Punch
From those ΔG values, QuantumCURE Pro™’s thermodynamic engine estimates IC50 in the:
Sub-nanomolar to low-nanomolar range
Several of these are labeled “Extremely Potent” (IC50 < 10 nM).The rest fall into “Highly Potent” (10–100 nM).
Translation for non-chemistry folks: These numbers are the kind of potency you’d love to see when you’re getting ready to call a wet lab and say, “Can you please synthesize this and see if we just got lucky… or if we just changed somebody’s future?”
3. Zero Toxicity Flags: Clean Sweep
Here’s the crazy part:
Toxicity Flags: None
All 11 compounds pass the toxicity filters
Usually, when you chase very strong binding, you start paying for it with:
Ugly structural alerts
PAINS motifs
“Yeah it binds… but it will also light up every red flag in your ADMET panel”
Not here.
This run gave me high-affinity binders with clean, drug-like profiles. That’s not normal. That’s what made me sit back in my chair and say, “Okay… this thing is really working.”
4. Quantum Confidence: 99% Across the Board
Every compound in this golden list is coming in with:
Quantum Confidence ≈ 0.99 (99%)
That’s my way of saying: Across repeated quantum-seeded runs, this pattern keeps showing up. This isn’t a one-off random fluke. The system likes this region of chemical space.
In other words, the quantum entropy harvested from https://cryptalabs.com/ hardware and the classical docking agree: these molecules are not noise. They’re multi-run survivors.
5. CRISP-G: The Quantum VIN Number for Each Hit
Every compound in this list is tagged with a full 24-character CRISP-G fingerprint and that is my: Clustered Randomness-Indexed Symbolic Pathway Glyph
Think of it as a VIN number for the quantum discovery pathway:
The front part of the glyph captures the shared “core story”, the pharmacophore and collapse pattern that the QRNG kept steering toward.
The tail of the glyph mutates as the system tweaks substituents, conformers, and pose variants , like an automatic R-group SAR campaign, written in symbols. Don't know what SAR Campaign and R-Group is? Well, I explained it at the bottom of this post.
Later, when a medicinal chemist asks,
“Why did your system pick this one, out of millions?”
…I don’t just show a docking score. I pull up the glyph evolution timeline and say:
“Here’s the exact symbolic path the quantum entropy followed to arrive at this hit.”
That’s not just docking. That’s quantum forensics.
6. Meet the Headliners
From this run, a few compounds rise to the top of the hit parade:
Compound 6378 – The Hammer
Best affinity (~−11.96 kcal/mol)
Sub-nanomolar predicted IC50
Clean toxicity and rock-solid profile
This is the one you put on the front slide when investors are in the room.
Compound 2724 – The Stability King
Almost identical affinity (~−11.92 kcal/mol)
Highest Collapse Score in the set
In quantum language: the energy landscape funnels toward this pose again and again. That often translates into better thermodynamic stability and residence time.
Compound 5791 – The Backup Sniper
Strong binding, high collapse score
Slightly different CRISP-G tail, giving me chemotype diversity in the same pocket
And here’s the punchline: not one of these is a known marketed EGFR drug. These are fresh structures living in QuantumCURE Pro’s search space.
7. What Happens Next?
I’m not stopping at pretty dashboards.
Here’s how I’m treating this golden list:
Physics Upgrade
Explicit-solvent MD on the top candidates
MM/GBSA rescoring to refine ΔG
Stress-test across EGFR mutants (L858R, T790M, C797S)
ADMET & Selectivity Pass
In-silico ADMET + hERG + CYP triage
Kinome selectivity profiling to see who else these molecules like to talk to
Wet-Lab Bridge
Shortlist for synthesis
Enzyme assays + cellular readouts
If I’m lucky: a co-crystal structure with one of my “garage molecules”
Investor & Citizen-Scientist Story
These 11 hits are proof that a retired storm-video engineer in Oklahoma, a hardware QRNG, and a custom quantum-symbolic engine can stand next to the big platforms……and find serious candidates.
8. Why I’m Posting This
I’m not posting this to say, “Look at my perfect model.” Models are never perfect.
I’m posting this to say:
“A solo developer with a quantum entropy pipeline, a symbolic glyph language, and a stubborn streak can now generate a pharma-grade hit list from a home office.”
If this is what I can do in 2025–2026 with one EGFR run, imagine:
This engine running 24/7 across multiple targets
Citizen scientists donating compute
Labs picking off the top CRISP-G hits
And a few years down the road… someone in a clinic getting a drug that started life as a line in my CSV and a glyph on my screen.
Bad to the bone? Yeah. But aimed straight at cancer.
— MansourQuantumLaso, LLC · QuantumCURE Pro™
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* R-group SAR campaign = “changing the side chains on purpose and watching what happens”
R-group = the side chain hanging off a core scaffold. In a SMILES or sketch, you’ve got a stable core (the part that actually sits in the hinge / key pocket), and you swap little pieces on the edges: methyl, ethyl, CF₃, Cl, OMe, etc. Those swappable side bits are called R-groups.
SAR (Structure–Activity Relationship) =“How does the structure change when I tweak X, and how does the biological activity respond?” Example: change CH₃ → Cl → CF₃ at one position and see binding go:
CH₃: −8.5 kcal/mol
Cl: −9.4
CF₃: −10.1That pattern is an SAR at that position.
Campaign =Systematic project: you design, dock/synthesize, and test a whole series of analogs where you deliberately vary R-groups around a fixed core to map out the SAR.
For harvesting true randomness in my docking engine, I rely on the QCicada USB Quantum Random Number Generator from Crypta Labs. It’s a photon-based QRNG: a calibrated light source and detector measure genuine quantum noise, which is then cleaned up by their on-board “QEngine” with real-time health tests and NIST 800-90B–compliant post-processing. The device delivers about 0.5 Mbit/s of independently verified entropy (~1,950 256-bit numbers per second), runs on a simple USB interface, and ships with excellent Python support, so it drops straight into my QuantumCURE Pro™ pipeline as a live entropy feed. In practice it has been rock-solid: stable across long runs, statistically clean, and reliable enough that I treat it as a small quantum lab on a stick sitting next to my workstation. cryptalabs.com+2cryptalabs.com+2
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