Identifying network motifs as drug targets from post-translational regulation networks

来源 :第五届全国生物信息学与系统生物学学术大会 | 被引量 : 0次 | 上传用户:wrdyh
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  Background: Post-translational modification (PTM) is one of the most important biological processes within cellular machines, the de-function of which may lead to devastating diseases.Identifying post-translational dysregulations can provide insights into the mechanisms underlying diseases, and help design more effective therapies.Since molecules generally work in concert, the post-translational regulation network (PTRN) can therefore help to elucidate the context in which enzymes regulate substrates and possible crosstalk between distinct post-translational regulations as well as how disease associated proteins and drug target proteins are regulated.Methods: In this work, we present a novel approach to identify network motifs that can be used as potential drug targets.To this end, a post-translational regulation network is assembled by collecting post-translational regulations from different sources, where the PTRN consists of two important PTMs: phosphorylation and hydrolysis.These two PTMs are considered here since they are two most common PTMs and are found to be related to many diseases, whereas kinases are widely used drug targets.Subsequently, network motifs are identified from the PTRN, which are then analyzed from both functional and network perspectives.Results: The analysis of the above-identified network motifs show that some of the network motifs are specifically enriched in disease associated genes.Further analysis show that these networks motifs are also enriched in drug targets.Therefore, these network motifs may serve as potential drug targets.In particular, we find that the crosstalk between kinases and proteases plays important roles in those regulation network motifs.Conclusions: There are some regulatory network motifs that are related to diseases and can serve as drug targets.The crosstalk between distinct PTMs can help to understand the mechanisms that underlie diseases and identify potential drug targets .
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