MolAttnNet: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention

MolAttnNet: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention

The solubility of a drug in water is a crucial indicator of its therapeutic efficacy and safety. However, traditional prediction methods often overlook the fine local structural dependencies within molecules, limiting the accuracy of solubility predictions. To address this issue, we propose MolAttnN...

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Bibliographic Details
Main Authors: Chenxu Wang, Yijun Feng, Zhejie Xu, Xiaohui Xu, Bangguo Peng
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Drug solubility
GNN
LSTM
transformer
deep learning
ADME
Online Access:https://ieeexplore.ieee.org/document/11113310/
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https://ieeexplore.ieee.org/document/11113310/

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