Sampling rare conformational transitions with a quantum computer.

ABSTRACT: Structural rearrangements play a central role in the organization and function of complex biomolecular systems. In principle, Molecular Dynamics (MD) simulations enable us to investigate these thermally activated processes with an atomic level of resolution. In practice, an exponentially large fraction of computational resources must be invested to simulate thermal fluctuations in metastable states. Path sampling methods focus the computational power on sampling the rare transitions between states. One of their outstanding limitations is to efficiently generate paths that visit significantly different regions of the conformational space. To overcome this issue, we introduce a new algorithm for MD simulations that integrates machine learning and quantum computing. First, using functional in

SUBMITTER: Ghamari D 

PROVIDER: S-EPMC9522734 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature