Predicting Motif-Mediated Interactions Based on Viral Genomic Composition

Sobia Idrees, Keshav Raj Paudel, Mithila Banik, Newton Suwal, Rajan Thapa, Saroj Bashyal

Research output: Contribution to journalArticlepeer-review

Abstract

Viruses manipulate host cellular machinery to propagate their life cycle, with one key strategy being the mimicry of short linear motifs (SLiMs) found in host proteins. While databases continue to expand with virus–host protein–protein interaction (vhPPI) data, accurately predicting viral mimicry remains challenging due to the inherent degeneracy of SLiMs. In this study, we investigate how viral genomic composition influences motif mimicry and the mechanisms through which viruses hijack host cellular functions. We assessed domain–motif interaction (DMI) enrichment differences, and also predicted new DMIs based on known viral motifs with varying stringency levels, using SLiMEnrich v.1.5.1. Our findings reveal that dsDNA viruses capture significantly more known DMIs compared to other viral groups, with dsRNA viruses also exhibiting higher DMI enrichment than ssRNA viruses. Additionally, we identified new vhPPIs mediated via SLiMs, particularly within different viral genomic contexts. Understanding these interactions is vital for elucidating viral strategies to hijack host functions, which could inform the development of targeted antiviral therapies.

Original languageEnglish
Article number3674
JournalInternational Journal of Molecular Sciences
Volume26
Issue number8
DOIs
Publication statusPublished - Apr 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 by the authors.

Keywords

  • bioinformatics
  • short linear motifs
  • viral mimicry
  • virus–host interactions

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