Sampling a Rare Protein Transition Using Quantum Annealing.

Simulating spontaneous structural rearrangements in macromolecules with classical molecular dynamics is an outstanding challenge. Conventional supercomputers can access time intervals of up to tens of μs, while many key events occur on exponentially longer time scales. Path sampling techniques have the advantage of focusing the computational power on barrier-crossing trajectories, but generating uncorrelated transition paths that explore diverse conformational regions remains a problem. We employ a hybrid path-sampling paradigm that addresses this issue by generating trial transition paths using a quantum annealing (QA) machine. We first employ a classical computer to perform an uncharted exploration of the conformational space. The data set generated in this exploration is then postprocessed using a path integral-based method to yield a coarse-grained network representation of the reactive kinetics. By resorting to a quantum annealer, quantum superposition can be exploited to encode all of the transition pathways in the initial quantum state, thus potentially solving the path exploration problem. Furthermore, each QA cycle yields a completely uncorrelated trial trajectory. We previously validated this scheme on a prototypically simple transition, which could be extensively characterized on a desktop computer. Here, we scale up in complexity and perform an all-atom simulation of a protein conformational transition that occurs on the millisecond time scale, obtaining results that match those of the Anton special-purpose supercomputer. Despite limitations due to the available quantum annealers, our study highlights how realistic biomolecular simulations provide potentially impactful new ground for applying, testing, and advancing quantum technologies.