Resource-Efficient Bio-Molecular Docking on a NISQ-era Digital Quantum Computer

Abstract:Molecular docking is a vital computational task in drug discovery, wherein the objective is to efficiently identify optimal binding poses between a ligand and a target receptor protein. Due to the combinatorial explosion of possible binding configurations, docking of large and flexible molecules remains a computationally intensive problem, especially at scale. Early studies have revealed that the molecular docking can be re-cast as a maximum vertex-weighted clique problem (MVWCP) problem on a compatibility graph to be solved classically. In this work, we proposed a hybrid quantum-classical approach for molecular docking leveraging the MVWCP formalism with a variational full-basis encoding (FBE) strategy, which enables efficient encoding of classical binary variables with Bloch sphere vectors. We further prove that a global minimizer of the FBE objective can always be chosen to be a pure product state, thereby providing a rigorous justification for its optimization using a unitary variational circuit. The molecular docking problem is first mapped to a cost Hamiltonian that is minimized within a variational framework, optimized via a randomized imaginary time evolution (ITE)-inspired warm start, and gradient-based techniques. Finally, we also executed the circuit on an IBM quantum computer, underlying the feasibility and of quantum-assisted optimization for structure-based drug design and point towards the broader utility of advanced encoding techniques in quantum optimization for computational biology.

Quantum Physics (quant-ph); Soft Condensed Matter (cond-mat.soft); Chemical Physics (physics.chem-ph); Biomolecules (q-bio.BM)

arXiv:2608.19868 [quant-ph]

(or arXiv:2608.19868v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.19868 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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