NMR-Based Quantum Molecular Simulation
A paradigm shift in computing binding energies — transforming how the pharmaceutical and materials science industries discover and design chemistry.
The Challenge
Determining binding energies involving metal ions — Fe, Cu, Mn, Co — represents one of the most intractable problems in pharmaceutical and materials science R&D. Classical computers face an insurmountable computational wall that makes accurate predictions practically impossible.
Electronic Complexity
Metal-center proteins involve intricate electron interactions distributed across many orbitals, creating a scale of quantum complexity that overwhelms classical approaches entirely.
The Computational Wall
Classical computers must enumerate millions of electron configurations per molecule. Even on powerful HPC clusters, each calculation can take weeks and consume enormous resources.
Precision Demands
The pharmaceutical industry requires chemical accuracy at ±0.5–1.0 kcal/mol to reliably distinguish promising drug candidates from failed compounds — a bar existing methods consistently miss.
The Vertical Wall Effect
Classical methods often fail to find any meaningful correlation between computed results and experimental potency — rendering all molecules computationally indistinguishable.
The Breakthrough
Qubicalz leverages the native capabilities of NMR quantum hardware to perform molecular simulations the way nature intended — directly in quantum space, using the molecular environment of an open system to solve the problem at its core.
Quantum Superposition — Native quantum hardware handles all electron configurations simultaneously, completely eliminating the exponential enumeration bottleneck.
VQE Ground State Finding — The Variational Quantum Eigensolver locates the molecular ground state efficiently, replacing computationally expensive classical matrix operations.
Direct Measurement — Our NMR quantum hardware directly measures electron density matrices (1-RDM and 2-RDM), bypassing reconstruction from vast wavefunction coefficients.
ML Calibration — Machine learning optimization refines predictions using measured quantum observables alongside known experimental data.
Why Qubicalz
Hours
Per Molecule
Versus weeks with classical methods — enabling high-throughput screening campaigns that were previously out of reach.
~10×
Cost Reduction
Dramatically lower compute costs per molecule compared to classical HPC approaches, making large-scale screening campaigns economically viable.
±0.5
kcal/mol Accuracy
Achieves the chemical accuracy threshold the pharma industry requires — while classical methods consistently fall short on real metalloprotein systems.
How It Works
Qubicalz delivers a complete QSaaS (Quantum Simulation as a Service) platform, enabling pharmaceutical and materials science organizations to run high-accuracy binding energy calculations on demand — with results in hours, not weeks.
Hamiltonian Construction
DFT-based algorithms build compact Hamiltonian representations of the active binding site, capturing the most chemically relevant degrees of freedom.
Quantum Measurement
VQE runs on NMR quantum hardware to directly measure one- and two-electron reduced density matrices — the key quantum descriptors for accurate binding affinity prediction.
Predictive Modeling
Q-QSAR models trained on experimental data translate quantum observables into accurate predictions of binding affinity (pKi, IC₅₀, ΔE) for novel drug candidates.
Applications
Qubicalz targets the most computationally challenging — and commercially significant — problems in modern chemistry, wherever metal-ion interactions define outcome.
Pharmaceutical R&D
Accelerate screening of metalloprotein-targeting drug candidates — kinases, cytochromes, metalloproteases — with binding affinity predictions that were previously computationally intractable.
Materials Science
Rational design of transition-metal catalysts for industrial chemistry, energy storage, and green chemistry applications — guided by accurate quantum simulations.
Oncology & Infectious Disease
Enable precision targeting of metalloenzymes implicated in cancer and infectious disease, expanding the druggable landscape for next-generation therapeutics.
Computational Chemistry
Integrate Qubicalz as a high-accuracy quantum layer into existing computational pipelines — replacing or augmenting classical CASSCF/CASPT2 calculations at a fraction of the cost.
The Team
Dr. Yoav Kimchy
Founder & CEO
B.Sc. in Physics and Mathematics, M.Sc. in Nuclear Magnetic Resonance, Ph.D. in Signal Processing. A proven track record of translating complex scientific breakthroughs into commercial products.
Tom Sax
General Counsel & VP Business Development
Experienced litigator and former CEO combining deep legal expertise in intellectual property with executive leadership in technology startups — specializing in strategic partnerships and commercialization of deep-tech innovations.
Ready to Explore?
Whether you're a pharmaceutical company, materials science organization, or research institution — we'd love to discuss how quantum molecular simulation can accelerate your programs.