1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Target prediction for GSK3β inhibitors in colorectal cancer pathway based on Morgan fingerprints
Paper ID : 1429-ICB10
Authors:
Zahra Jannat doust1, Salva Golgoun1, Gerhard Wolber1, Mostafa Zakariazadeh2, Somaieh Soltani *1
1Department of Medicinal Chemistry, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
2Department of Biology, Faculty of Sciences, Payame Noor University, Tehran, Iran
Abstract:
Colorectal cancer is associated with inflammation. A systematic data-mining [1] study was performed to investigate colorectal cancer related targets for inhibitors of GSK3β. Morgan fingerprints were calculated for all studied compounds. Tanimoto index was calculated using fingerprints and compounds with Tanimoto >0.7 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 Chembl25. According to the results some GSK3β inhibitors can be an inhibitor for AKT, IKKA, PKB and CDK1 as well. The reliability of the results was evaluated using the available evidences for the inhibition of predicted targets from literature and the survey showed that there is published evidences for the inhibition of IKKα, PKB and CDK1. The mode of interaction of the compounds with the highest and lowest potency were evaluated using molecular docking methods and the results indicated good correlation with experimental results. In conclusion the developed method is reliable for the target prediction.
Keywords:
Colorectal cancer; inflammation; GSK3β; knime platform; molecular docking
Status : Paper Accepted (Poster Presentation)