Pretrained Models
BBB
CYP450
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D-CyPre: Tool for Accurately Predicting the Site of Metabolism of Human Cytochrome P450 Metabolism
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GTransCYPs: graph transformer neural network with attention pooling for reliably predicting CYP450 inhibitors
General
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ADMET_XGBoost: ADMETboost: a web server for accurate ADMET prediction
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ADMETlab: systematical evaluation of ADMET properties, as well as some physicochemical properties and medicinal chemistry friendliness
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ADMETlab3.0: systematical evaluation of ADMET properties, as well as some physicochemical properties and medicinal chemistry friendliness
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ChemMORT: ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization
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OCHEM:
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QIP: Machine learning model that predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of molecules.
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SwissADME: web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness
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VEGA:
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admet-ai: ADMET-AI: A machine learning ADMET platform for evaluation of large-scale chemical libraries
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vNN-ADMET:
Metabolites
PK
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Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction
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PKSmart: This work used molecular structural fingerprints, physicochemical properties, and predicted animal PK data as features to model the human PK parameters VDss, CL, t½, fu and MRT for 1,283 unique compounds and developed a webhosted application PKSmart, the first work that publicly releases PK models on par with industry-standard models.
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pkCSM:
Toxicity
Toxicity
hERG
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CLOP-hERG: Contrastive Learning Optimized Pretrained Model for Representation Learning in Predicting Drug-Induced hERG Channel Blockers
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CardioTox: A robust predictor for hERG channel blockade via deep learning meta ensembling approaches
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hERGdb: web-based cardiotoxicity prediction