Pissurlenkar Raghuvir R S, Shaikh Mushtaque S, Coutinho Evans C
Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai, India.
J Mol Model. 2007 Oct;13(10):1047-71. doi: 10.1007/s00894-007-0227-2. Epub 2007 Aug 4.
Dipeptidyl peptidase IV (DPP-IV) deactivates the incretin hormones GLP-1 and GIP by cleaving the penultimate proline or alanine from the N-terminal (P1-position) of the peptide. Inhibition of this enzyme will prevent the degradation of the incretin hormones and maintain glucose homeostasis; this makes it an attractive target for the development of drugs for diabetes. This paper reports 3D-QSAR analysis of several DPP-IV inhibitors, which were aligned by the receptor-based technique. The conformation of the molecules in the active site was obtained through docking methods. The QSAR models were generated on two training sets composed of 74 and 25 molecules which included phenylalanine, thiazolidine, and fluorinated pyrrolidine analogs. The 3D-QSAR models are robust with statistically significant r(2), q(2), and r(pred)(2) values. The CoMFA and CoMSIA models were used to design some new inhibitors with several fold higher binding affinity.
二肽基肽酶IV(DPP-IV)通过从肽的N端(P1位)切割倒数第二个脯氨酸或丙氨酸来使肠促胰岛素激素GLP-1和GIP失活。抑制这种酶将阻止肠促胰岛素激素的降解并维持葡萄糖稳态;这使其成为糖尿病药物开发的一个有吸引力的靶点。本文报道了几种DPP-IV抑制剂的3D-QSAR分析,这些抑制剂通过基于受体的技术进行比对。活性位点中分子的构象通过对接方法获得。QSAR模型是在由74个和25个分子组成的两个训练集上生成的,这些分子包括苯丙氨酸、噻唑烷和氟化吡咯烷类似物。3D-QSAR模型稳健,具有统计学上显著的r(2)、q(2)和r(pred)(2)值。CoMFA和CoMSIA模型用于设计一些结合亲和力高几倍的新抑制剂。