Predicting Motif-Mediated Interactions Based on Viral Genomic Composition

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.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-04-13
DOI
https://doi.org/10.3390/ijms26083674
Citations
1
Primary Topic
Bacteriophages and microbial interactions
Type
article
Field-Weighted Citation Impact
1.72
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article

Predicting Motif-Mediated Interactions Based on Viral Genomic Composition

Newton Suwal, Keshav Raj Paudel, Saroj Bashyal, Sobia Idrees et al.
1 citations
International Journal of Molecular Sciences
Bacteriophages and microbial interactions
1.72
article

Predicting Motif-Mediated Interactions Based on Viral Genomic Composition

Newton Suwal, Keshav Raj Paudel, Saroj Bashyal, Sobia Idrees, Mithila Banik, Rajan Thapa
article en
1 citations

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.

International Journal of Molecular SciencesVol. 26(8)
University of Technology Sydney (AU), Asian University for Women (BD), Tribhuvan University (NP), Centenary Institute (AU), College of Medical Sciences (NP), UNSW Sydney (AU)
Responsible consumption and production
Openalex Percentile: Top 18%
Bacteriophages and microbial interactions
1.72
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Predicting Motif-Mediated Interactions Based on Viral Genomic Composition — Newton Suwal, Keshav Raj Paudel, et al. · International Journal of Molecular Sciences (2025) | TGRS Research Map | TGRS