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README.md
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tags:
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- biology
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- chemistry
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library_name: tdc
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license: mit
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---
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## Dataset description
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An integrated Ether-a-go-go-related gene (hERG) dataset consisting of molecular structures
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## Task description
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Binary classification. Given a drug SMILES string, predict whether it blocks (1, <10uM) or not blocks (0, >=10uM).
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## Dataset statistics
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Total: 13445; Train_val: 12620; Test: 825
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## Dataset split
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Random split
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To load the dataset in TDC, type
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```
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## Model description
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AttentiveFP is a Graph Attention Network-based molecular representation learning method.
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To load the pre-trained model, type
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tdc_hf.predict_deeppurpose(dp_model, ['CC(=O)NC1=CC=C(O)C=C1'])
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```
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## References
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tags:
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- biology
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- chemistry
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- therapeutic science
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- drug design
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- drug development
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- therapeutics
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library_name: tdc
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license: mit
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---
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## Dataset description
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An integrated Ether-a-go-go-related gene (hERG) dataset consisting of molecular structures labeled as hERG (<10uM) and non-hERG (>=10uM) blockers in the form of SMILES strings was obtained from the DeepHIT, the BindingDB database, ChEMBL bioactivity database, and other literature.
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## Task description
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Binary classification. Given a drug SMILES string, predict whether it blocks (1, <10uM) or not blocks (0, >=10uM).
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## Dataset statistics
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Total: 13445; Train_val: 12620; Test: 825
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## Dataset split
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Random split with 70% training, 10% validation, and 20% testing
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To load the dataset in TDC, type
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```
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## Model description
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AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
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To load the pre-trained model, type
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tdc_hf.predict_deeppurpose(dp_model, ['CC(=O)NC1=CC=C(O)C=C1'])
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```
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## References
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* Dataset entry in Therapeutics Data Commons, https://tdcommons.ai/single_pred_tasks/tox.
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* Karim, A., et al. CardioTox net: a robust predictor for hERG channel blockade based on deep learning meta-feature ensembles. J Cheminform 13, 60 (2021). https://doi.org/10.1186/s13321-021-00541-z
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