Prediction of the water solubility by a graph convolutional-based neural network on a highly curated dataset

Prediction of the water solubility by a graph convolutional-based neural network on a highly curated dataset

Abstract Water solubility is a relevant physico-chemcial property in environmental chemistry, toxicology, and drug design. Although the water solubility is besides the octanol–water partition coefficient, melting point, and boiling point a property with a large amount of available experimental data,...

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Bibliographic Details
Main Authors: Nadin Ulrich, Karsten Voigt, Anton Kudria, Alexander Böhme, Ralf-Uwe Ebert
Format: Article
Language:English
Published: BMC 2025-04-01
Series:Journal of Cheminformatics
Subjects:
Water solubility
Neural networks
Machine learning
Physico-chemical property prediction
Online Access:https://doi.org/10.1186/s13321-025-01000-9
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https://doi.org/10.1186/s13321-025-01000-9

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