Ramatenki Vishwanath, Dumpati Ramakrishna, Vadija Rajender, Vellanki Santhiprada, Potlapally Sarita Rajender, Rondla Rohini, Vuruputuri Uma
Department of Chemistry, University College of Science, Osmania University, Hyderabad, Telangana, 500007, India.
Department of Chemistry, Nizam College, Osmania University, Basheerbagh, Hyderabad, Telangana, 500001, India.
Appl Biochem Biotechnol. 2017 Aug;182(4):1497-1517. doi: 10.1007/s12010-017-2414-7. Epub 2017 Feb 9.
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.
癌症的特征是细胞异常生长。在发现新的抗癌疗法中靶向泛素蛋白是一种有吸引力的策略。本研究使用基于结构的药物发现方法来鉴定对假定的泛素结合酶E2N样蛋白（UBE2NL）具有选择性的新先导结构。使用同源建模技术评估UBE2NL的三维结构。使用标准的计算机模拟方法对模型进行验证。通过蛋白质-蛋白质对接研究确定了UBE2NL中有助于与其天然受体泛素结合酶E2变体（UBE2V）结合的疏水口袋。使用活性位点预测工具确定UBE2NL的结合位点区域。对接研究考虑了负责癌细胞进展的UBE2NL的结合位点。针对UBE2NL的活性位点对小分子结构数据库进行虚拟筛选研究。对显示出对UBE2NL有亲和力的配体分子进行ADME预测研究。优先考虑符合Lipinski五规则和Jorgensen三规则等药代动力学性质（如人体口服吸收等）的配体分子。所得的配体分子可考虑用于开发用于癌症治疗的强效UBE2NL酶抑制剂。
