2025/12/09 by Daniele Loco, Kisa Barkemeyer, Loco, Daniele +5 · 1 voice · 1 citation
Physics and Astronomy · #Biological Physics (physics.bio-ph) #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #Quantum Physics (quant-ph) #physics.bio-ph #physics.chem-ph #quant-ph
paper · pdf · doi:10.48550/arxiv.2512.08390
published as Physical Review Research, 2026
arxiv created 2025/12/11 · arxiv updated 2026/07/30
Demonstrating the practical utility of Noisy Intermediate-Scale Quantum (NISQ) hardware for recurrent tasks in Computer-Aided Drug Discovery is of paramount importance. We tackle this challenge by performing three-dimensional protein pockets hydration-site prediction on a quantum computer. Formulating the water placement problem as a Quadratic Unconstrained Binary Optimization (QUBO), we use a hybrid approach coupling a classical three-dimensional reference-interaction site model (3D-RISM) to an efficient quantum optimization solver, to run various hardware experiments up to 123 qubits. Matching the precision of classical approaches, our results reproduced experimental predictions on real-life protein-ligand complexes. Furthermore, through a detailed resource estimation analysis, we show that accuracy can be systematically improved with increasing number of qubits, indicating that full quantum utility is in reach. Finally, we provide evidence that advantageous situations could be found for systems where classical optimization struggles to provide optimal solutions. The method has potential for assisting simulations of protein-ligand complexes for drug lead optimization and setup of docking calculations.