Chauhan Pallavi, Shakya Madhvi
Department of Bioinformatics,MANIT, Bhopal, MP, India.
Bioinformation. 2009 Nov 26;4(6):223-8. doi: 10.6026/97320630004223.
Literature shows that various molecular cascades are activated by stress, UV rays and pollutants leading to wrinkle formation of the skin. These cascades start from five types of receptors (EGFR, PDGFR, PAFR, IL1R, TNFRB) and terminate with the production of matrix metalloproteinase's, which degrades collagen leading to wrinkle formation. Signaling pathway leading to wrinkle formation showed that c-jun is involved in these cascades. Therefore, c-jun is the preferential choice for inhibition to reduce the intensity of collagen degradation. Hence, the 3D structure of c-jun was modeled using segment based homology modeling by MODELLER 9v5. Evaluation of the constructed model was done by PROCHECK, WHAT CHECK and through RMSD/RMSF calculations. Ligands for the inhibitory sites were designed using LIGANDSCOUT. The interaction study of ligand and receptor was performed by AUTODOCK. A library of analogues was constructed for three known inhibitory sites. The receptor-analogue study was performed using the software MOLEGRO Virtual Docker. The analogues constructed from the designed novel reference ligands showed good binding with the receptor binding sites. It should be noted that these predicted data should be validated using suitable assays for further consideration.
文献表明,压力、紫外线和污染物会激活各种分子级联反应,导致皮肤形成皱纹。这些级联反应从五种类型的受体(表皮生长因子受体、血小板衍生生长因子受体、血小板活化因子受体、白细胞介素-1受体、肿瘤坏死因子受体β)开始,最终产生基质金属蛋白酶,该酶会降解胶原蛋白,导致皱纹形成。导致皱纹形成的信号通路表明,c-jun参与了这些级联反应。因此,c-jun是抑制胶原蛋白降解强度的首选靶点。因此,使用MODELLER 9v5基于片段的同源建模方法对c-jun的三维结构进行了建模。通过PROCHECK、WHAT CHECK以及RMSD/RMSF计算对构建的模型进行评估。使用LIGANDSCOUT设计抑制位点的配体。通过AUTODOCK进行配体与受体的相互作用研究。针对三个已知的抑制位点构建了类似物库。使用软件MOLEGRO Virtual Docker进行受体-类似物研究。由设计的新型参考配体构建的类似物与受体结合位点表现出良好的结合。需要注意的是,这些预测数据应使用合适的分析方法进行验证,以供进一步研究参考。