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A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network

HuanHuan Cao¹, YuHang Zhang², Jia Zhao³

¹Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China.

Combinatorial Chemistry & High Throughput Screening

|March 16, 2017

Abstract

Background:

Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous.

Objective:

According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm.

Conclusion:

We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes.

Keywords:

Ebola virus GO enrichment betweenness human protein identification pathogenic mechanism shortest path

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