October 12, 2025Open Access

Quantum Machine Learning for Drug Discovery: From Molecular Descriptors to Explainable Quantum Pharmacology

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Hybrid approach improves ligand-target binding predictions in drug discovery, highlighting quantum pharmacology's implications.

Quantum embeddings in drug discovery achieve competitive predictive accuracy and improved stability.
A synthetic dataset reflecting BindingDB was used to evaluate the performance of quantum descriptors.
Comparative analyses with classical methods revealed quantum models’ potential in predicting ligand-target binding.
Explainable Quantum Pharmacology emphasizes the importance of interpretability alongside accuracy in drug discovery.

Volkan Erol (2025) studied this question.

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October 12, 2025Open Access

View Full Paper

Ask AI

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Authors

Hybrid approach improves ligand-target binding predictions in drug discovery, highlighting quantum pharmacology's implications.

Quantum embeddings in drug discovery achieve competitive predictive accuracy and improved stability.
A synthetic dataset reflecting BindingDB was used to evaluate the performance of quantum descriptors.
Comparative analyses with classical methods revealed quantum models’ potential in predicting ligand-target binding.
Explainable Quantum Pharmacology emphasizes the importance of interpretability alongside accuracy in drug discovery.

Volkan Erol (2025) studied this question.

View Full Paper

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Bookmark