整合素黏附体信号转导通路预测研究

目的运用生物信息学方法预测整合素黏附体信号蛋白间的信号转导通路,为以实验方法研究整合素相关信号转导通路的机制提供参考。方法把相互作用的整合素黏附体信号分子对搭建成相互作用网络;利用相互作用的置信概率构建边权;然后,采用动态规划算法计算出最小权重的线性通路,再把这些线性通路组装成通路网络。结果从147个整合素黏附体蛋白所组成的736对相互作用中预测出7个信号通路网络,并计算出各个通路网络中基因本体论注释蛋白的占有率。结论对信号转导通路的研究能够在分子水平上探索疾病的发病机制。预测出可能的信号通路网络,不仅为基础医学研究疾病机制提供有用信息,也为探索包括力学、化学等外界信号刺激下的信号转导通路提供有益参考信息。

Prediction study on signal transduction pathways of integrin adhesome

Objective To predict signal transduction pathways of the integrin adhesome via bioinformatics method, so as to provide references for experimental study on the mechanism of integrin-related signal transduction pathways. Methods First, the interaction network between the interactive integrin adhesome was constructed, and the confidence probability of each interaction was used as its link weight, respectively. Secondly, the pathways of the minimum weight were identified via a standard dynamic programming algorithm. Finally, all pathways calculated by the algorithm were aggregated into some probable networks. Results Seven signal transduction pathways were obtained from the integrin adhesome interaction network that contained 147 components with 736 interactions. In every predicted signal transduction pathway, the coverage rate of the proteins with Gene Ontology annotation was calculated. Conclusions By research on signal transduction pathways the pathogenesis of some diseases can be explored at the molecular level. Several possible signal transduction pathways obtained in this study have some reference value for exploring disease mechanism in basic medical sciences, and also provide some useful information for such exploration under the stimulation of external signals including mechanical or chemical signals.