Personalized human protein interactomes

蛋白质-蛋白质相互作用(PPI)对细胞的生物功能至关重要。本课题组开发的蛋白质相互作用预测引擎(PIPE)算法是目前最敏感的基于基因组序列的PPI预测方法。高通量测序技术很快将能够确定每个人独特的基因组序列。由于蛋白质相互作用在疾病和药物作用中起着关键作用，确定个体序列变异对其个人蛋白质组的影响将是实现真正个性化药物的重要一步。我们建议开发一种新的个性化交互作用组管道(PIPE-PIP)算法和软件，该算法和软件将能够确定给定个体的基因(基因组)的完整蛋白质组，重点是该个体基因组特有的一组序列变异。我们计划使用PIPE-PIP为1000基因组计划中的1000个个体基因组构建蛋白质组。然后，我们将开发算法和软件来比较这些蛋白质组，并将蛋白质组变化(可能导致疾病的原因)与基因组中的序列变异联系起来。

Protein-protein interactions (PPIs) are critical to the biological functioning of a cell. The Protein Interaction Prediction Engine (PIPE) algorithm developed by our group is currently the most sensitive genome sequence based method for PPI prediction. High-throughput sequencing technologies will soon enable the determination of each person's unique genome sequence. Since protein interactions play a critical role in disease and the functioning of drugs, determining the implications of an individual's sequence variants on their personal proteome will be a significant step towards achieving truly personalized medicine. We propose to develop a new Personalized Interactome Pipeline (PIPE-PIP) algorithm and software that will be able to determine an individual's complete proteome given their genotype (genome), focusing on the set of sequence variants specific to that individual's genome. We plan to use PIPE-PIP to build the proteomes for 1000 individual genomes from the 1000 Genomes Project. We will then develop algorithms and software to compare those proteomes and correlate proteome changes (possible cause for disease) to sequence variations in the genomes.