Zahra Jannat Doust - Department of Medicinal Chemistry, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
Salva Golgoun - Department of Medicinal Chemistry, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
Gerhard Wolber - Pharmaceutical and Medicinal Chemistry (Computer-Aided Drug Design), Institute of Pharmacy, FreieUniversität Berlin, Berlin, Germany
Mostafa Zakariazadeh - Department of Biology, Faculty of Sciences, Payame Noor University, Tehran, Iran
Samira Shafiee - Department of Medicinal Chemistry, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran

Colorectal cancer is associated with inflammation. A systematic data-mining study was performed toinvestigate colorectal cancer related targets for inhibitors of GSK۳β. Morgan fingerprints were calculated forall studied compounds. Tanimoto index was calculated using fingerprints and compounds with Tanimoto>۰.۷ was indicated as similar. The developed procedure for target prediction was run using knime platform.RDKit and Chemaxon were used to fingerprint calculation. The inhibitors were extracted from Chembl۲۵.According to the results some GSK۳β inhibitors can be an inhibitor for AKT, IKKA, PKB and CDK۱ aswell. The reliability of the results was evaluated using the available evidences for the inhibition of predictedtargets from literature and the survey showed that there is published evidences for the inhibition of IKKα,PKB and CDK۱. The mode of interaction of the compounds with the highest and lowest potency wereevaluated using molecular docking methods and the results indicated good correlation with experimentalresults. In conclusion the developed method is reliable for the target prediction.

Colorectal cancer; inflammation; GSK۳β; knime platform; molecular docking