Q-CTRL

#compchem #quantumcomputing New paper published in Physical Review research: "Practical protein-pocket hydration-site prediction for drug discovery on a quantum computer". Great collaboration with @qubit_pharma and @qctrlHQ ! Here are the key takeaways from this work: 🔬Formulating the Problem: We mapped the 3D hydration-site prediction task onto a Quadratic Unconstrained Binary Optimization (QUBO) problem by fitting 3D Reference Interaction Site Model (3D-RISM) continuous water densities into a Gaussian Mixture Model (GMM). ⚡ Demonstrating Scale on Real Quantum Hardware:Ran hardware experiments on 156-qubit IBM Heron processors using Q-CTRL’s Fire Opal optimization solver. Successfully scaled up to 123 qubits to solve 3D water placement in real-life protein-ligand complexes (FDA-approved drug target sites). Matched the accuracy of classical approaches while achieving significantly higher success probabilities than traditional simulated annealing (SA) heuristics on hardware. 📈 Path to Quantum Utility: Detailed resource estimations reveal that accuracy systematically improves as the problem scale expands toward ~900+ qubits. With rapid developments in hardware and early error correction, full quantum advantage for CADD setup tasks, such as molecular docking and lead optimization, is approaching. A massive thank you to co-authors: @loco_daniele, Kisa Barkemeyer, Andre R. R. Carvalho for driving this forward! 📄 Read the full paper here: doi.org/10.1103/gyqr-mvlh