Molecular Docking via Weighted Subgraph Isomorphism on Quantum Annealers

TL;DR

This paper formulates molecular docking as a weighted subgraph isomorphism problem suitable for quantum annealing, comparing quantum and classical annealing methods for drug discovery.

Contribution

It introduces a novel QUBO formulation for molecular docking based on weighted subgraph isomorphism and evaluates quantum annealing performance against classical methods.

Findings

Quantum annealers show competitive performance with classical solvers.

The formulation captures ligand flexibility and geometrical properties.

Results demonstrate potential of quantum approaches in drug discovery.

Abstract

Molecular docking is an essential step in the drug discovery process involving the detection of three-dimensional poses of a ligand inside the active site of the protein. In this paper, we address the Molecular Docking search phase by formulating the problem in QUBO terms, suitable for an annealing approach. We propose a problem formulation as a weighted subgraph isomorphism between the ligand graph and the grid of the target protein pocket. In particular, we applied a graph representation to the ligand embedding all the geometrical properties of the molecule including its flexibility, and we created a weighted spatial grid to the 3D space region inside the pocket. Results and performance obtained with quantum annealers are compared with classical simulated annealing solvers.