A Scalable Heuristic for Molecular Docking on Neutral-Atom Quantum Processors

• URL: http://arxiv.org/abs/2508.18147v1
• Date: Mon, 25 Aug 2025 15:54:52 GMT
• Title: A Scalable Heuristic for Molecular Docking on Neutral-Atom Quantum Processors
• Authors: Mathieu Garrigues, Victor Onofre, Wesley Coelho, S. Acheche,
• Abstract summary: We show how a novel divide-and-conquer algorithm can be used to solve large-scale docking problems.<n>Our work paves the way for tackling large-scale docking challenges on near-term quantum hardware.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Molecular docking is a critical computational method in drug discovery used to predict the binding conformation and orientation of a ligand within a protein's binding site. Mapping this challenge onto a graph-based problem, specifically the Maximum Weighted Independent Set (MWIS) problem, allows it to be addressed by specialized hardware such as neutral-atom quantum processors. However, a significant bottleneck has been the size mismatch between biologically relevant molecular systems and the limited capacity of near-term quantum devices. In this work, we overcome this scaling limitation by the use of a novel divide-and-conquer heuristic introduced in Cazals et al. This algorithm enables the solution of large-scale MWIS problems by decomposing a single, intractable graph instance into smaller sub-problems that can be solved sequentially on a neutral-atom quantum emulator, incurring only a linear computational overhead. We demonstrate the power of this approach by solving a 540-node MWIS problem representing the docking of an inhibitor to the Tumor necrosis factor-$\alpha$ Converting Enzyme--thiol-containing Aryl Sulfonamide (TACE-AS) complex. Our work enables the application of quantum methods to more complex and physically realistic molecular systems than previously possible, paving the way for tackling large-scale docking challenges on near-term quantum hardware.

Related papers

• Resource Estimation for VQE on Small Molecules: Impact of Fermion Mappings and Hamiltonian Reductions [0.0]
  Variational Quantumsolver (VQE) represents a leading hybrid quantum-classical paradigm for addressing this challenge.<n>Resource requirements for VQE implementations employing the Unitary Coupled Cluster Singles and Doubles (UCCSD) ansatz are systematically analyzed.<n>Hamiltonian reduction strategies, including $mathbbZ$ tapering and frozen-core approximations, are examined to assess their effect on quantum resource scaling.
  arXiv  Detail & Related papers  (2025-12-01T12:24:00Z)
• Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing [36.94429692322632]
  We develop an algorithm that exploits the complex absorbing potential formalism to distill the problem of molecular resonance identification into a network of hybrid quantum-classical variational quantum eigensolver tasks.<n>We show qDRIVE successfully identifies resonance energies and wavefunctions in simulated quantum processors with current and planned specifications.
  arXiv  Detail & Related papers  (2025-11-20T02:28:05Z)
• The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design [0.0]
  We introduce the Quantum Ensemble Variational Optimization (QEVO) method for near-term and early fault-tolerant quantum computing platforms.<n>QEVO efficiently maps molecular structures onto an orthonormal basis of Pauli strings and samples from a superposition state.<n>Our numerical simulations demonstrate the potential of QEVO in designing drug-like molecules with anticancer properties.
  arXiv  Detail & Related papers  (2025-08-21T18:00:12Z)
• Graph Algorithms with Neutral Atom Quantum Processors [31.546387965618333]
  We review the advancements in quantum algorithms for graph problems running on neutral atom Quantum Processing Units (QPUs) We discuss recently introduced embedding and problem-solving techniques. We clarify ongoing advancements in hardware, with an emphasis on enhancing the scalability, controllability and repetition rate of neutral atom QPUs.
  arXiv  Detail & Related papers  (2024-03-18T16:30:42Z)
• Quantum benefit of the quantum equation of motion for the strongly coupled many-body problem [0.0]
  The quantum equation of motion (qEOM) is a hybrid quantum-classical algorithm for computing excitation properties of a fermionic many-body system. We demonstrate explicitly that the qEOM exhibits a quantum benefit due to the independence of the number of required quantum measurements.
  arXiv  Detail & Related papers  (2023-09-18T22:10:26Z)
• A hybrid quantum-classical algorithm for multichannel quantum scattering of atoms and molecules [62.997667081978825]
  We propose a hybrid quantum-classical algorithm for solving the Schr"odinger equation for atomic and molecular collisions. The algorithm is based on the $S$-matrix version of the Kohn variational principle, which computes the fundamental scattering $S$-matrix. We show how the algorithm could be scaled up to simulate collisions of large polyatomic molecules.
  arXiv  Detail & Related papers  (2023-04-12T18:10:47Z)
• Bootstrap Embedding on a Quantum Computer [4.138095344167023]
  We extend molecular bootstrap embedding to make it appropriate for implementation on a quantum computer. We show how a quadratic speedup can be obtained over the classical algorithm, in principle.
  arXiv  Detail & Related papers  (2023-01-04T05:49:15Z)
• Towards Neural Variational Monte Carlo That Scales Linearly with System Size [67.09349921751341]
  Quantum many-body problems are central to demystifying some exotic quantum phenomena, e.g., high-temperature superconductors. The combination of neural networks (NN) for representing quantum states, and the Variational Monte Carlo (VMC) algorithm, has been shown to be a promising method for solving such problems. We propose a NN architecture called Vector-Quantized Neural Quantum States (VQ-NQS) that utilizes vector-quantization techniques to leverage redundancies in the local-energy calculations of the VMC algorithm.
  arXiv  Detail & Related papers  (2022-12-21T19:00:04Z)
• Experimental quantum computational chemistry with optimised unitary coupled cluster ansatz [23.6818896497932]
  Experimental realisation of scalable and high-precision quantum chemistry simulation remains elusive. We push forward the limit of experimental quantum computational chemistry and successfully scale up the implementation of VQE with an optimised unitary coupled-cluster ansatz to 12 qubits.
  arXiv  Detail & Related papers  (2022-12-15T18:04:28Z)
• Coarse grained intermolecular interactions on quantum processors [0.0]
  We develop a coarse-grained representation of the electronic response that is ideally suited for determining the ground state of weakly interacting molecules. We demonstrate our method on IBM superconducting quantum processors. We conclude that current-generation quantum hardware is capable of probing energies in this weakly bound but nevertheless chemically ubiquitous and biologically important regime.
  arXiv  Detail & Related papers  (2021-10-03T09:56:47Z)
• Hardware-Efficient, Fault-Tolerant Quantum Computation with Rydberg Atoms [55.41644538483948]
  We provide the first complete characterization of sources of error in a neutral-atom quantum computer. We develop a novel and distinctly efficient method to address the most important errors associated with the decay of atomic qubits to states outside of the computational subspace. Our protocols can be implemented in the near-term using state-of-the-art neutral atom platforms with qubits encoded in both alkali and alkaline-earth atoms.
  arXiv  Detail & Related papers  (2021-05-27T23:29:53Z)
• Optimizing Electronic Structure Simulations on a Trapped-ion Quantum Computer using Problem Decomposition [41.760443413408915]
  We experimentally demonstrate an end-to-end pipeline that focuses on minimizing quantum resources while maintaining accuracy. Using density matrix embedding theory as a problem decomposition technique, and an ion-trap quantum computer, we simulate a ring of 10 hydrogen atoms without freezing any electrons. Our experimental results are an early demonstration of the potential for problem decomposition to accurately simulate large molecules on quantum hardware.
  arXiv  Detail & Related papers  (2021-02-14T01:47:52Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.