Karimpour-Fard Anis, Hunter Lawrence, Gill Ryan T
Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, Colorado 80045, USA.
BMC Genomics. 2007 Oct 29;8:393. doi: 10.1186/1471-2164-8-393.
The use of computational methods for predicting protein interaction networks will continue to grow with the number of fully sequenced genomes available. The Co-Conservation method, also known as the Phylogenetic profiles method, is a well-established computational tool for predicting functional relationships between proteins.
Here, we examined how various aspects of this method affect the accuracy and topology of protein interaction networks. We have shown that the choice of reference genome influences the number of predictions involving proteins of previously unknown function, the accuracy of predicted interactions, and the topology of predicted interaction networks. We show that while such results are relatively insensitive to the E-value threshold used in defining homologs, predicted interactions are influenced by the similarity metric that is employed. We show that differences in predicted protein interactions are biologically meaningful, where judicious selection of reference genomes, or use of a new scoring scheme that explicitly considers reference genome relatedness, produces known protein interactions as well as predicted protein interactions involving coordinated biological processes that are not accessible using currently available databases.
These studies should prove valuable for future studies seeking to further improve phylogenetic profiling methodologies as well for efforts to efficiently employ such methods to develop new biological insights.
随着可用的全基因组序列数量的增加,用于预测蛋白质相互作用网络的计算方法的使用将会持续增长。共保守方法,也称为系统发育谱方法,是一种用于预测蛋白质之间功能关系的成熟计算工具。
在这里,我们研究了该方法的各个方面如何影响蛋白质相互作用网络的准确性和拓扑结构。我们已经表明,参考基因组的选择会影响涉及先前未知功能蛋白质的预测数量、预测相互作用的准确性以及预测相互作用网络的拓扑结构。我们表明,虽然这些结果对定义同源物时使用的E值阈值相对不敏感,但预测的相互作用会受到所采用的相似性度量的影响。我们表明,预测的蛋白质相互作用差异具有生物学意义,其中明智地选择参考基因组,或使用明确考虑参考基因组相关性的新评分方案,会产生已知的蛋白质相互作用以及涉及使用当前可用数据库无法获得的协调生物过程的预测蛋白质相互作用。
这些研究对于未来寻求进一步改进系统发育谱方法的研究以及有效利用此类方法以获得新的生物学见解的努力应具有重要价值。