Quantum molecular unfolding

Kevin Mato

doi:10.1088/2058-9565/ac73af

Quantum molecular unfolding

2022-06-09

7

OA

AI

DOI：10.1088/2058-9565/ac73af

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Molecular docking is an important step of the drug discovery process which aims at calculating the preferred position and shape of one molecule to a second when they are bound to each other. During such analysis, 3D representations of molecules are manipulated according to their degree of freedoms: rigid roto-translation and fragment rotations along the rotatable bonds. In our work, we focussed on one specific phase of the molecular docking procedure i.e. molecular unfolding (MU), which is used to remove the initial bias of a molecule by expanding it to an unfolded shape simpler to manipulate within the target cavity. The objective of the MU problem is to find the configuration that maximizes the molecular area, or equivalently, that maximizes the internal distances between atoms inside the molecule. We propose a quantum annealing approach to MU by formulating it as a high-order unconstrained binary optimization which was possible to solve on the latest D-wave annealing hardware (2000Q and advantage). Results and performances obtained with quantum annealers are compared with state of art classical solvers.

Keyword:

molecular docking

combinatorial optimization

high performance computing

simulated annealing

quantum annealing

molecular unfolding

quantum computing

Quantum molecular unfolding

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