Naqsh e Zahra Syeda, Khattak Naureen Aslam, Mir Asif
Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan.
Theor Biol Med Model. 2013 Jan 1;10:1. doi: 10.1186/1742-4682-10-1.
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.
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.
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.
肺癌是全球主要的死亡原因。在肺癌治疗中可能发挥重要作用的主要信号通路包括：（1）促生长通路（表皮生长因子受体/ Ras /磷脂酰肌醇3 -激酶）；（2）生长抑制通路（p53 / Rb / P14ARF，STK11）；（3）凋亡通路（Bcl - 2 / Bax / Fas / FasL）。通过应用比较建模和分子对接研究，实施了计算机模拟策略来解开选定肺癌通路背后的谜团。
利用YASARA [v 12.4.1] 分别使用模板4ELJ - A和1MX6 - B预测P16 - INK4和RB1基因的结构模型。WHAT CHECK评估工具显示预测的P16 - INK4和RB1的整体质量，Z分数分别为 - 0.132和 - 0.007，这强烈表明结构预测可靠。利用STRING服务器探索蛋白质 - 蛋白质相互作用，结果表明，基于置信度得分分别为0.999和0.999，CDK4和E2F1与P16 - INK4和RB1表现出强烈的相互作用。为了全面了解候选基因与其功能相互作用分子之间的复杂相互作用，使用了GRAMM - X服务器。P16 - INK4的蛋白质 - 蛋白质对接研究揭示了四个离子键，表明Arg47、Arg80、Cys72和Met1残基积极参与与CDK4的相互作用，而RB1的对接结果显示四个氢键，涉及Glu864、Ser567、Asp36和Arg861残基，它们与其各自的功能相互作用分子E2F1强烈相互作用。
本研究可能为理解P16 - INK4和RB1蛋白的生物学见解提供基础，这将有助于未来设计合适的药物来抑制疾病发病机制，因为我们已经确定了可作为靶点的相互作用氨基酸，以便在体外设计配体，为临床试验提出药物。候选基因及其重要相互作用残基的蛋白质 - 蛋白质对接可能为开发计算机辅助药物设计提供途径。
