Quantum QSAR for drug discovery
Keywords:
QSAR, classification, drug discovery, support vector machines, quantum kernelAbstract
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 in 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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Copyright (c) 2025 Alejandro Giraldo, Daniel Ruiz, Mariano Caruso, Guido Bellomo
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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