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Review
. 2023:21:1774-1784.
doi: 10.1016/j.csbj.2023.02.044. Epub 2023 Feb 27.

Bioinformatics approaches for unveiling virus-host interactions

Hitoshi Iuchi  1   2 , Junna Kawasaki  3 , Kento Kubo  2   4 , Tsukasa Fukunaga  5 , Koki Hokao  4 , Gentaro Yokoyama  2   4 , Akiko Ichinose  1 , Kanta Suga  4 , Michiaki Hamada  1   2   4   6
Affiliations
Review

Bioinformatics approaches for unveiling virus-host interactions

Hitoshi Iuchi et al. Comput Struct Biotechnol J. 2023.

Abstract

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

Keywords: Host range prediction; Protein–protein interaction prediction; Virus–host interaction.

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Figures

Fig. 1
Fig. 1
Conceptual diagram of (A) virus-host prediction and (B) PPI prediction. Solid lines indicate known interaction pairs (typically by experiment), and dashed lines indicate predicted interaction pairs.
See this image and copyright information in PMC

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