Author:
e Zahra Syeda Naqsh,Khattak Naureen Aslam,Mir Asif
Abstract
Abstract
Background
Lung cancer is the major cause of mortality worldwide. Major signalling pathways that could play significant role in lung cancer therapy include (1) Growth promoting pathways (Epidermal Growth Factor Receptor/Ras/ PhosphatidylInositol 3-Kinase) (2) Growth inhibitory pathways (p53/Rb/P14ARF, STK11) (3) Apoptotic pathways (Bcl-2/Bax/Fas/FasL). Insilico strategy was implemented to solve the mystery behind selected lung cancer pathway by applying comparative modeling and molecular docking studies.
Results
YASARA [v 12.4.1] was utilized to predict structural models of P16-INK4 and RB1 genes using template 4ELJ-A and 1MX6-B respectively. WHAT CHECK evaluation tool demonstrated overall quality of predicted P16-INK4 and RB1 with Z-score of −0.132 and −0.007 respectively which showed a strong indication of reliable structure prediction. Protein-protein interactions were explored by utilizing STRING server, illustrated that CDK4 and E2F1 showed strong interaction with P16-INK4 and RB1 based on confidence score of 0.999 and 0.999 respectively. In order to facilitate a comprehensive understanding of the complex interactions between candidate genes with their functional interactors, GRAMM-X server was used. Protein-protein docking investigation of P16-INK4 revealed four ionic bonds illustrating Arg47, Arg80,Cys72 and Met1 residues as actively participating in interactions with CDK4 while docking results of RB1 showed four hydrogen bonds involving Glu864, Ser567, Asp36 and Arg861 residues which interact strongly with its respective functional interactor E2F1.
Conclusion
This research may provide a basis for understanding biological insights of P16-INK4 and RB1 proteins which will be helpful in future to design a suitable drug to inhibit the disease pathogenesis as we have determined the interacting amino acids which can be targeted in order to design a ligand in-vitro to propose a drug for clinical trials. Protein -protein docking of candidate genes and their important interacting residues likely to be provide a gateway for developing computer aided drug designing.
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Modelling and Simulation
Reference10 articles.
1. Herbst RS, Heymach JV, Lippman SM: Lung cancer. N Engl J Med. 2008, 359: 1367-1380. 10.1056/NEJMra0802714.
2. Brenner DR, McLaughlin JR, Rayjean J, Hung RJ: Previous lung diseases and lung cancer risk: a systematic review and meta-analysis. PLoS One. 2011, 3: e17479-
3. Hackshaw KA, Law RM, Wald JN: The accumulated evidence on lung cancer and environmental tobacco smoke. BMJ. 1997, 315: 980-10.1136/bmj.315.7114.980.
4. Blot WJ, McLaughlin JK: Passive smoking and lung cancer risk: what is the story now. J Natl Cancer Inst. 1998, 90: 1416-1417. 10.1093/jnci/90.19.1416.
5. Kohno T, Otsuka A, Girard L, Sato M, Iwakawa R, Ogiwara H, Cespedes MS, Minna JD, Yokota J: A Catalog of Genes Homozygously Deleted in Human Lung Cancer and the Candidacy of PTPRD as a Tumor Suppressor Gene. Genes Chromosomes Cancer. 2010, 4: 342-352.
Cited by
26 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献