RNA-protein interaction prediction using network-guided deep learning Article Swipe
Haoquan Liu
,
Yiren Jian
,
Chen Zeng
,
Yunjie Zhao
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s42003-025-07694-9
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s42003-025-07694-9
Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models for RNA-protein interaction prediction. Here, we introduce ZHMolGraph, which integrates graph neural network and unsupervised large language models to predict RNA-protein interaction. We validate ZHMolGraph predictions on two benchmark datasets and outperform the current best methods. For the dataset of entirely unknown RNAs and proteins, ZHMolGraph shows an improvement in achieving high AUROC of 79.8% and AUPRC of 82.0%. This represents a substantial improvement of 7.1%-28.7% in AUROC and 4.6%-30.0% in AUPRC over other methods. We utilize ZHMolGraph to enhance the challenging SARS-CoV-2 RPI and unbound RNA-protein complex predictions. Such enhancements make ZHMolGraph a reliable option for genome-wide RNA-protein prediction. ZHMolGraph holds broad potential for modeling and designing RNA-protein complexes.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s42003-025-07694-9
- OA Status
- gold
- Cited By
- 13
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407605420
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407605420Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1038/s42003-025-07694-9Digital Object Identifier
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RNA-protein interaction prediction using network-guided deep learningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-02-16Full publication date if available
- Authors
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Haoquan Liu, Yiren Jian, Chen Zeng, Yunjie ZhaoList of authors in order
- Landing page
-
https://doi.org/10.1038/s42003-025-07694-9Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://doi.org/10.1038/s42003-025-07694-9Direct OA link when available
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Deep learning, Computational biology, Artificial intelligence, Computer science, RNA, Biology, Genetics, GeneTop concepts (fields/topics) attached by OpenAlex
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13Total citation count in OpenAlex
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2025: 13Per-year citation counts (last 5 years)
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49Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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