School of Computing, Clemson University, Clemson, SC 29634, USA.
Proteome Sci. 2012 Jun 21;10 Suppl 1(Suppl 1):S4. doi: 10.1186/1477-5956-10-S1-S4.
Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear.
In this study we used the clusters of short polypeptide sequences, which are typically shorter than the classically defined protein domains, to characterize the functionalities of proteins. We developed a framework to identify significant short polypeptide clusters from yeast protein sequences, and then used these short polypeptide clusters as features to predict yeast synthetic lethal genetic interactions. The short polypeptide clusters based approach provides much higher coverage for predicting yeast synthetic lethal genetic interactions. Evaluation using experimental data sets showed that the short polypeptide clusters based approach is superior to the previous protein domain based one.
We were able to achieve higher performance in yeast synthetic lethal genetic interactions prediction using short polypeptide clusters as features. Our study suggests that the short polypeptide cluster may help better understand the functionalities of proteins.
蛋白质合成致死遗传相互作用可用于定义蛋白质和途径之间的功能关系。然而,合成致死遗传相互作用的分子机制尚不清楚。
在这项研究中,我们使用了短多肽序列簇,这些序列簇通常比经典定义的蛋白质结构域短,用于表征蛋白质的功能。我们开发了一种从酵母蛋白序列中识别显著短多肽簇的框架,然后使用这些短多肽簇作为特征来预测酵母合成致死遗传相互作用。基于短多肽簇的方法为预测酵母合成致死遗传相互作用提供了更高的覆盖率。使用实验数据集进行评估表明,基于短多肽簇的方法优于基于先前蛋白质结构域的方法。
我们能够使用短多肽簇作为特征在酵母合成致死遗传相互作用预测中实现更高的性能。我们的研究表明,短多肽簇可能有助于更好地理解蛋白质的功能。