Fong Jessica H, Keating Amy E, Singh Mona
Computer Science Department and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Olden Street, Princeton, NJ 08544, USA.
Genome Biol. 2004;5(2):R11. doi: 10.1186/gb-2004-5-2-r11. Epub 2004 Jan 16.
We present a method for predicting protein-protein interactions mediated by the coiled-coil motif. When tested on interactions between nearly all human and yeast bZIP proteins, our method identifies 70% of strong interactions while maintaining that 92% of predictions are correct. Furthermore, cross-validation testing shows that including the bZIP experimental data significantly improves performance. Our method can be used to predict bZIP interactions in other genomes and is a promising approach for predicting coiled-coil interactions more generally.
我们提出了一种预测由卷曲螺旋基序介导的蛋白质-蛋白质相互作用的方法。当在几乎所有人类和酵母bZIP蛋白之间的相互作用上进行测试时，我们的方法识别出了70%的强相互作用，同时保持92%的预测是正确的。此外，交叉验证测试表明，纳入bZIP实验数据显著提高了性能。我们的方法可用于预测其他基因组中的bZIP相互作用，并且是一种更广泛地预测卷曲螺旋相互作用的有前景的方法。
