Enhancing molecular property prediction with quantized GNN models
Abstract Efficient and reliable prediction of molecular properties, such as water solubility, hydration free energy, lipophilicity, and quantum mechanical properties, is essential for rational compound design in the chemical and pharmaceutical industries. While Graph Neural Networks (GNNs) have sign...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
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| Series: | Journal of Cheminformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13321-025-00989-3 |
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