DILI-StK

DILI Predictor

The liver is a primary organ for xenobiotics metabolism and thereby is susceptible to toxic compounds. Thus, there is a demand for an accurate in silico prediction model for hepatotoxicity of drug candidates for successful drug development. We developed a drug-induced liver injury (DILI) prediction model using a large-scale hepatotoxicity dataset. This model can assist in successful drug discovery by predicting the DILI in the drug screening step.

DILI Predictor

The liver is a primary organ for xenobiotics metabolism and thereby is susceptible to toxic compounds. Thus, there is a demand for an accurate in silico prediction model for hepatotoxicity of drug candidates for successful drug development. We developed a drug-induced liver injury (DILI) prediction model using a large-scale hepatotoxicity dataset. This model can assist in successful drug discovery by predicting the DILI in the drug screening step.

Server Submission
Because DILI-Stk calculates molecular descriptors by relying on SMILES (Simplified Molecular-Input Line-Entry System), jobs can currently only be submitted by using SMILES.
Please enter correct SMILES. To predict the toxicity of multiple molecules simultaneously, the SMILES file with the extension '.smi' can alternatively be queried. For this query file, please input SMILES line by line. Input SMILES: or Submit .SMI File:

Citation: Lee, J., Yu, M., and Na, D. DILI-Stk: An Ensemble Model for the Prediction of Drug-induced Liver Injury of Drug Candidates. Current Bioinformatics 17,3 (2022)

Bug reports: blisszen [at] cau.ac.kr

School of integrative engineering
Chung-Ang University, Korea