Abstract
Cancer is characterized by abnormal growth of cells. Targeting ubiquitin proteins in the discovery of new anticancer therapeutics is an attractive strategy. The present study uses the structure-based drug discovery methods to identify new lead structures, which are selective to the putative ubiquitin-conjugating enzyme E2N-like (UBE2NL). The 3D structure of the UBE2NL was evaluated using homology modeling techniques. The model was validated using standard in silico methods. The hydrophobic pocket of UBE2NL that aids in binding with its natural receptor ubiquitin-conjugating enzyme E2 variant (UBE2V) was identified through protein-protein docking study. The binding site region of the UBE2NL was identified using active site prediction tools. The binding site of UBE2NL which is responsible for cancer cell progression is considered for docking study. Virtual screening study with the small molecular structural database was carried out against the active site of UBE2NL. The ligand molecules that have shown affinity towards UBE2NL were considered for ADME prediction studies. The ligand molecules that obey the Lipinski’s rule of five and Jorgensen’s rule of three pharmacokinetic properties like human oral absorption etc. are prioritized. The resultant ligand molecules can be considered for the development of potent UBE2NL enzyme inhibitors for cancer therapy.
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Acknowledgements
The author VR acknowledges Council of Scientific and Industrial Research (CSIR)-INDIA for the financial support (File No: 09/132(0821)/2012-EMR-I). The author RV acknowledges Council of Scientific and Industrial Research (CSIR)-INDIA for SRF. The authors RKD and SPV acknowledge UGC for SRF under RFSMS scheme. The author RR acknowledges UGC for PDF. The authors also acknowledge Principal and Head, Department of Chemistry, University College Science, Osmania University, Hyderabad for providing facilities to carry out this work.
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Ramatenki, V., Dumpati, R., Vadija, R. et al. Identification of New Lead Molecules Against UBE2NL Enzyme for Cancer Therapy. Appl Biochem Biotechnol 182, 1497–1517 (2017). https://doi.org/10.1007/s12010-017-2414-7
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DOI: https://doi.org/10.1007/s12010-017-2414-7