Target prediction based on multi-category Naive Bayesian ChEMBL_24 models.

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Step 1: Draw a compound or put a SMILES code to text area.

Step 2: Complete the form

Step 3: click button SUBMIT

Step 4: As long as the prediction job is finished, the result will be sent to your email. Just click the link in the email.

How to read results

Multi-category Naive Bayesian ChEMBL_24 models was used to predict the potential targets which were ranked according to probability (Proba value in the report file).


1. Xia X, Maliski EG, Gallant P, Rogers D. Classification of Kinase Inhibitors Using a Bayesian Model. J Med Chem. 2004;47(18):4463-4470. doi:10.1021/jm0303195.

2. Nidhi, Glick M, Davies JW, Jenkins JL. Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases. J Chem Inf Model. 2006;46(3):1124-1133. doi:10.1021/ci060003g

3. Clark AM, Ekins S. Open Source Bayesian Models. 2. Mining a “Big Dataset” To Create and Validate Models with ChEMBL. J Chem Inf Model. 2015;55(6):1246-1260. doi:10.1021/acs.jcim.5b00144

4. Gaulton A, Hersey A, Nowotka ML, et al. The ChEMBL database in 2017. Nucleic Acids Res. 2017. doi:10.1093/nar/gkw1074

5. ChEMBL(Version 24).