1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Target prediction for the inhibitors of VEGFR2 as anti-colorectal cancer compounds using similarity-based search methods
Paper ID : 1463-ICB10
Authors:
Samira Shafiee1, Andreas Bender2, Mostafa Zakariazadeh3, David Schaller4, Somaieh Soltani *1
1Department of Medicinal chemistry, Pharmacy Faculty, Tabriz university of medical sciences, Tabriz, Iran
22 Department of Chemistry, Centre for Molecular Informatics, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
3دپارتمان زیست- دانشکده علوم- دانشگاه پیام نور- تهران- ایران
4In silico Toxicology and Structural Bioinformatics, Institute of Physiology, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
Abstract:
Colorectal cancer is among the diseases that little is known about its etiology. Like other cancers, colorectal cancer is the end result of a multifactorial, multi genetic, and multistage process. VEGFR2 has been indicated as a key factor of angiogenesis in many cancers as well as colorectal cancer. Its inhibition is under investigation as anti-angiogenesis cancer therapy. To investigate the multi-targeting characteristic of VEGFR2 inhibitors, we utilized a rational approach combined with similarity-based search methods to the prediction of targets from a list of colorectal cancer-related drug targets. Data mining workflow was developed using KNIME. The data was extracted from the ChEMBL25 database. The Morgan fingerprints were calculated by RDKit and ChemAxon. Tanimoto similarity index was calculated and the clustering of the inhibitors was done using a procedure implemented by KNIME. Proper activity thresholds and Tanimoto index were optimized based on the obtained results and the method was validated using the available evidence for the probable inhibition of the predicted targets from literature. Compounds were considered similar if the Tanimoto score was > 0.7. Using the developed method, CDK2, HER1, and TGF-β2 were predicted for the investigated VEGFR2 inhibitors. CDK2 was predicted for AT-9283, as a multi-targeted VEGFR2 inhibitor using the developed method, there is published evidence for the inhibition of CDK2 by AT-9283 which approves the prediction capability of the developed method. In addition, we studied the interaction of AT-9283 with VGEFR2 and CDK2 using molecular docking and the obtained binding energy values were -9.20 Kcal/mol and -9.60 Kcal/mol, respectively. The results from the molecular docking study were in good agreement with reported experiments. According to the results, the developed method could be used for the target prediction with high reliability.
Keywords:
Colorectal cancer; Multi-target; KNIME platform; Molecular docking; VGEFR2
Status : Paper Accepted (Oral Presentation)