Quantum QSAR for drug discovery

Alejandro Giraldo, Daniel Ruiz, Mariano Caruso, Guido Bellomo
5/6/2025
quant-phcs.LG

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Abstract

Quantitative Structure-Activity Relationship (QSAR) modeling is key in drug discovery, but classical methods face limitations when handling high-dimensional data and capturing complex molecular interactions. This research proposes enhancing QSAR techniques through Quantum Support Vector Machines (QSVMs), which leverage quantum computing principles to process information Hilbert spaces. By using quantum data encoding and quantum kernel functions, we aim to develop more accurate and efficient predictive models.

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Cite this paper

@article{giraldo2025quantum,
  title  = {Quantum QSAR for drug discovery},
  author = {Alejandro Giraldo and Daniel Ruiz and Mariano Caruso and Guido Bellomo},
  year   = {2025},
  eprint = {2505.04648},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.04648v2}
}

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