Integrating Multifaceted Information to Predict Mycobacterium tuberculosis-Human Protein-Protein Interactions

结核分枝杆菌 蛋白质-蛋白质相互作用 计算生物学 肺结核 细菌蛋白 生物 医学 细菌 遗传学 病理
作者
Jun Sun,Lingli Yang,Xi Chen,Kong De,Rong Liu
出处
期刊:Journal of Proteome Research [American Chemical Society]
卷期号:17 (11): 3810-3823 被引量:9
标识
DOI:10.1021/acs.jproteome.8b00497
摘要

Tuberculosis (TB) is one of the biggest infectious disease killers caused by Mycobacterium tuberculosis (MTB). Studying the protein-protein interactions (PPIs) between MTB and human can deepen our understanding of the pathogenesis of TB and offer new clues to the treatment against MTB infection, but the experimentally validated interactions are especially scarce in this regard. Herein we proposed an integrated framework that combined template-, domain-domain interaction-, and machine learning-based methods to predict MTB-human PPIs. As a result, we established a network composed of 13 758 PPIs including 451 MTB proteins and 3167 human proteins ( http://liulab.hzau.edu.cn/MTB/ ). Compared to known human targets of various pathogens, our predicted human targets show a similar tendency in terms of the network topological properties and enrichment in important functional genes. Additionally, these human targets largely have longer sequence lengths, more protein domains, more disordered residues, lower evolutionary rates, and older protein ages. Functional analysis demonstrates that these proteins show strong preferences toward the phosphorylation, kinase activity, and signaling transduction processes and the disease and immune related pathways. Dissecting the cross-talk among top-ranked pathways suggests that the cancer pathway may serve as a bridge in MTB infection. Triplet analysis illustrates that the paired targets interacting with the same partner are adjacent to each other in the intraspecies network and tend to share similar expression patterns. Finally, we identified 36 potential anti-MTB human targets by integrating known drug target information and molecular properties of proteins.
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