# Molecular Docking with Gaussian Boson Sampling

## TL;DR

This paper demonstrates that Gaussian Boson Samplers can be used to predict molecular docking configurations, potentially aiding drug discovery by efficiently identifying stable binding poses in complex molecular systems.

## Contribution

It introduces a novel approach using Gaussian Boson Samplers to solve the molecular docking problem by sampling large-weight cliques in a graph, improving prediction of binding configurations.

## Key findings

- Gaussian Boson Samplers can sample stable docking configurations with high probability.
- The approach enhances classical algorithms for molecular docking.
- Benchmarking on a target enzyme shows promising results.

## Abstract

Gaussian Boson Samplers are photonic quantum devices with the potential to perform tasks that are intractable for classical systems. As with other near-term quantum technologies, an outstanding challenge is to identify specific problems of practical interest where these quantum devices can prove useful. Here we show that Gaussian Boson Samplers can be used to predict molecular docking configurations: the spatial orientations that molecules assume when they bind to larger proteins. Molecular docking is a central problem for pharmaceutical drug design, where docking configurations must be predicted for large numbers of candidate molecules. We develop a vertex-weighted binding interaction graph approach, where the molecular docking problem is reduced to finding the maximum weighted clique in a graph. We show that Gaussian Boson Samplers can be programmed to sample large-weight cliques, i.e., stable docking configurations, with high probability, even in the presence of photon loss. We also describe how outputs from the device can be used to enhance the performance of classical algorithms and increase their success rate of finding the molecular binding pose. To benchmark our approach, we predict the binding mode of a small molecule ligand to the tumor necrosis factor-${\alpha}$ converting enzyme, a target linked to immune system diseases and cancer.