Quantum Computing Simulation of Complex Molecular Dynamics for Drug Design

Abstract

Accurate simulation of protein-ligand binding dynamics remains computationally prohibitive for classical computers when exploring conformational spaces spanning millions of degrees of freedom. We present a hybrid quantum-classical workflow that leverages 127-qubit superconducting processors for variational quantum eigensolver (VQE) calculations of binding pocket electronic structure, coupled with classical molecular dynamics (MD) for conformational sampling. Applied to three kinase targets (EGFR, JAK2, BRAF), the quantum-enhanced pipeline identifies lead compounds with predicted binding affinities within 0.8 kcal/mol of experimental values — a 3.2× improvement over classical docking alone. The workflow processes 10,000 candidate ligands in 72 hours on a hybrid cloud infrastructure, demonstrating practical utility for early-stage drug discovery campaigns.