Tanwar Omprakash, Deora Girdhar Singh, Tanwar Lalima, Kumar Gautam, Janardhan Sridhara, Alam Mumtaz, Akhter Mymoona
Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, Faculty of Pharmacy and Bioinformatics Infrastructure Facility (BIF), Jamia Hamdard, New Delhi, 110062, India.
J Mol Model. 2014 Apr;20(4):2118. doi: 10.1007/s00894-014-2118-7. Epub 2014 Apr 1.
The present study demonstrates and validates the discovery of two novel hydrazine derivatives as selective dipeptidyl peptidase-IV (DPP-IV) inhibitors. Virtual screening (VS) of publicly available databases was performed using virtual screening workflow (VSW) of Schrödinger software against DPP-IV and the most promising hits were selected. Selectivity was further assessed by docking the hits against homology modeled structures of DPP8 and DPP9. Two novel hydrazine derivatives were selected for further studies based on their selectivity threshold. To assess their correct binding modes and stability of their complexes with enzyme, molecular dynamic (MD) simulation studies were performed against the DPP-IV protein and the results revealed that they had a better binding affinity towards DPP-IV as compared to DPP 8 and DPP 9. The binding poses were further validated by docking these ligands with different softwares (Glide and Gold). The proposed binding modes of hydrazines were found to be similar to sitagliptine and alogliptine. Thus, the study reveals the potential of hydrazine derivatives as highly selective DPP-IV inhibitors.
本研究证明并验证了两种新型肼衍生物作为选择性二肽基肽酶-IV(DPP-IV)抑制剂的发现。使用薛定谔软件的虚拟筛选工作流程(VSW)对公开可用数据库进行针对DPP-IV的虚拟筛选,并选择了最有前景的命中物。通过将命中物与DPP8和DPP9的同源建模结构对接,进一步评估了选择性。基于它们的选择性阈值,选择了两种新型肼衍生物进行进一步研究。为了评估它们与酶形成复合物的正确结合模式和稳定性,对DPP-IV蛋白进行了分子动力学(MD)模拟研究,结果表明,与DPP 8和DPP 9相比,它们对DPP-IV具有更好的结合亲和力。通过使用不同软件(Glide和Gold)将这些配体对接,进一步验证了结合姿势。发现肼的拟结合模式与西他列汀和阿格列汀相似。因此,该研究揭示了肼衍生物作为高选择性DPP-IV抑制剂的潜力。