Welcome to ProTox-II, a virtual lab for the prediction of toxicities of small molecules.
The prediction of compound toxicities is an important part of the drug design development process. Computational toxicity estimations are not only faster than the determination of toxic doses in animals, but can also help to reduce the amount of animal experiments.
To read more about reducing animal testing, go to Animal Ethics 3R.
ProTox-II incorporates molecular similarity, fragment propensities, most frequent features and (fragment similarity based CLUSTER cross-validation) machine-learning, based a total of 33 models for the prediction of various toxicity endpoints such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes (Tox21) pathways and toxicity targets.
To predict the toxicity of a compound, please click here.
For a description of the server, methods and tutorials, go to FAQ.
To see statistics about our training set as well as the cross-validation results, please go to Statistics and Model info.
To learn more about the different models, look into Models
Should you have further questions, do not hesitate to contact us!
Predict compound toxicity
ProTox-II enables uncomplicated predictions of different levels of toxicities. To conduct a toxicity prediction, please click on the image.
Toxic doses and toxicity classes
Toxic doses are often given as LD50 values in mg/kg body weight. The LD50 is the median lethal dose meaning the dose at which 50% of test subjects die upon exposure to a compound.
Toxicity classes are defined according to the globally harmonized system of classification of labelling of chemicals (GHS). LD50 values are given in [mg/kg]:
Class I: fatal if swallowed (LD50 ≤ 5)
Class II: fatal if swallowed (5 < LD50 ≤ 50)
Class III: toxic if swallowed (50 < LD50 ≤ 300)
Class IV: harmful if swallowed (300 < LD50 ≤ 2000)
Class V: may be harmful if swallowed (2000 < LD50 ≤ 5000)
Class VI: non-toxic (LD50 > 5000)
Banerjee P., Eckert O.A., Schrey A.K., Preissner R.:
ProTox-II: a webserver for the prediction of toxicity of chemicals.
Nucleic Acids Res (Web server issue 2018);
Banerjee P , Dehnbostel F.O and Preissner R :
Prediction is a Balancing Act: Importance of Sampling Methods to Balance Sensitivity and Specificity of Predictive Models based on Imbalanced Chemical Data Sets Front. Chem
Drwal M.N., Banerjee P., Dunkel M., Wettig M.R., Preissner R.:
ProTox: a web server for the in silico prediction of rodent oral toxicity
Nucleic Acids Res (Web server issue 2014);
Toxicity targets are protein targets which have been associated with adverse drug reactions and toxic effects. Here, we predict possible binding to toxicity targets using a collection of protein-ligand-based pharmacophores.
To learn more about the paharmacophore based models, look into Models
To see warning about possible toxicity targets of your input compound, please click on
Toxicity targets Prediction.
The Tox21 (Toxicology in the 21st Century) platform tested chemicals for activity across a wide range of assays that target cellular processess. The goal of the initiative to prioritize substances for further in-depth toxicological evaluation as well as identify mechanisms of actions for further investigation such as disease-associated pathways.
To read more about Tox21 Program, go to Tox21 consortium.
To learn more about the machine laerning based prediction models, look into Models
To see warning about possible interference of your input compound in the toxicological pathways, please click on
Toxicological pathways Prediction.