Bioinformatics approaches for unveiling virus-host interactions

Hitoshi Iuchi*, Junna Kawasaki, Kento Kubo, Tsukasa Fukunaga, Koki Hokao, Gentaro Yokoyama, Akiko Ichinose, Kanta Suga, Michiaki Hamada

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish
Pages (from-to)1774-1784
Number of pages11
JournalComputational and Structural Biotechnology Journal
Publication statusPublished - 2023 Jan


  • Host range prediction
  • Protein–protein interaction prediction
  • Virus–host interaction

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications


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