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病毒-宿主蛋白相互作用预测的计算方法综述:以新型埃博拉病毒-人类相互作用为例

Review of computational methods for virus-host protein interaction prediction: a case study on novel Ebola-human interactions.

机构信息

Department of Computer Science and Engineering, Jadavpur University, India.

出版信息

Brief Funct Genomics. 2018 Nov 26;17(6):381-391. doi: 10.1093/bfgp/elx026.

Abstract

Identification of potential virus-host interactions is useful and vital to control the highly infectious virus-caused diseases. This may contribute toward development of new drugs to treat the viral infections. Recently, database records of clinically and experimentally validated interactions between a small set of human proteins and Ebola virus (EBOV) have been published. Using the information of the known human interaction partners of EBOV, our main objective is to identify a set of proteins that may interact with EBOV proteins. Here, we first review the state-of-the-art, computational methods used for prediction of novel virus-host interactions for infectious diseases followed by a case study on EBOV-human interactions. The assessment result shows that the predicted human host proteins are highly similar with known human interaction partners of EBOV in the context of structure and semantics and are responsible for similar biochemical activities, pathways and host-pathogen relationships.

摘要

鉴定潜在的病毒-宿主相互作用对于控制具有高度传染性的病毒疾病非常有用和至关重要。这有助于开发治疗病毒感染的新药。最近,已经发表了一小部分人类蛋白质与埃博拉病毒 (EBOV) 之间经过临床和实验验证的相互作用的数据库记录。利用已知的 EBOV 人类相互作用伙伴的信息,我们的主要目标是确定一组可能与 EBOV 蛋白相互作用的蛋白质。在这里,我们首先回顾了用于预测传染病新型病毒-宿主相互作用的最先进的计算方法,然后对 EBOV-人类相互作用进行了案例研究。评估结果表明,预测的人类宿主蛋白在结构和语义上与 EBOV 的已知人类相互作用伙伴非常相似,并且负责相似的生化活性、途径和宿主-病原体关系。

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