# QFold: Quantum Walks and Deep Learning to Solve Protein Folding

arXiv: https://arxiv.org/abs/2101.10279 · HTML: https://mlsanity.com/paper/2101.10279/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 70 references that are in the map.
- First posted on arXiv 25 Jan 2021.

## Builds on (most cited first, 2 of 2)

- [Quantum Google in a Complex Network](https://mlsanity.com/paper/1303.3891/) (2013)
- [Quantum Circuit Designs of Integer Division Optimizing T-count and T-depth](https://mlsanity.com/paper/1809.09732/) (2018)

## Built on by (most cited first, 5 of 5)

- [Data is often loadable in short depth: Quantum circuits from tensor networks for finance, images, fluids, and proteins](https://mlsanity.com/paper/2309.13108/) (2023)
- [Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling](https://mlsanity.com/paper/2106.03126/) (2021)
- [Advances in Machine Learning: Where Can Quantum Techniques Help?](https://mlsanity.com/paper/2507.08379/) (2025)
- [A quantum learning approach based on Hidden Markov Models for failure scenarios generation](https://mlsanity.com/paper/2204.00087/) (2022)
- [Quantum Metropolis Solver: A Quantum Walks Approach to Optimization Problems](https://mlsanity.com/paper/2207.06462/) (2022)

## Abstract (arXiv)

Predicting the 3D structure of proteins is one of the most important problems in current biochemical research. In this article, we explain how to combine recent deep learning advances with the well known technique of quantum walks applied to a Metropolis algorithm. The result, QFold, is a fully scalable hybrid quantum algorithm that, in contrast to previous quantum approaches, does not require a lattice model simplification and instead relies on the much more realistic assumption of parameterization in terms of torsion angles of the amino acids. We compare it with its classical analog for different annealing schedules and find a polynomial quantum advantage, and implement a minimal realization of the quantum Metropolis in the IBMQ Casablanca quantum system.