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Cited by 0RNA Research and SplicingGenomics and Phylogenetic StudiesRNA and protein synthesis mechanisms

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PRIME-BSPre: a genome-wide protein-RNA binding sites prediction method based on templates

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Wei, Xinhang, Duan, Yingtian, Li, Danyang, Liu, Xudong, Xie, Juan, Liu, Shiyong·2026·BMC Genomics
DOI 10.1186/s12864-026-12657-3PMC PMC13032426

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Abstract

In this paper, we present PRIME-BSPre, a template-based genome-wide method for predicting protein-RNA binding sites that incorporates the RNA sequence and secondary structure as well as the tertiary structure of corresponding RBPs. We are pioneers in introducing low Shannon entropy algorithm in PRIME-BSPre to describe the binding preferences of RBPs on RNA motifs. The LS-PEAK derived from LS-Scores in PRIME-BSPre is utilized to optimize the alignments screening. PRIME-BSPre has been successfully benchmarked on the human genome, demonstrating its excellent prediction performance on independent RBP datasets and its robustness across different cell lines.

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Fig. 1 Workflow of PRIME-BSPre. The input target is aligned with all the templates in template library. Tertiary structure similarity of RBPs, binding preference of binding sites, global and local similarity of RNA sequences and secondary structure are considered in PRIME-BSPre scoring methods. The alignment results are initially ranked by the LS-Scores and five best alignments are finally selected by the LS-PEAK as the prediction results
Fig. 1 Workflow of PRIME-BSPre. The input target is aligned with all the templates in template library. Tertiary structure similarity of RBPs, binding preference of binding sites, global and local similarity of RNA sequences and secondary structure are considered in PRIME-BSPre scoring methods. The alignment results are initially ranked by the LS-Scores and five best alignments are finally selected by the LS-PEAK as the prediction resultsCC BY · PubMed Central
Fig. 2 Local secondary structure and sequence features extracted on RNA binding sites. The pink-shaded region in the RNA secondary structure represents the binding sites, while LS-Score quantitatively assesses sequence and secondary structure similarities within this area between templates and targets. A The secondary structure HAIRPIN LOOP, which exhibits typical characteristics, is depicted along with its quantitative features. B The secondary structure MULTIPLE LOOP, which exhibits another characteristic feature, is depicted along with its corresponding quantitative attributes. C shows the Sequence features of native and predicted RNA binding sites: Motif Structure, Motif Sequence and Motif Set. Among them, Motif Structure is the Position Probability Matrices (PPMs) generated by serialized secondary structure features: B (Bulge), E (External strand), H (Hairpin loop), M (Multiple loop) and S (Stem); Motif set is a sequential description of all binding preference motifs, where each base represents the base enriched in motifs
Fig. 2 Local secondary structure and sequence features extracted on RNA binding sites. The pink-shaded region in the RNA secondary structure represents the binding sites, while LS-Score quantitatively assesses sequence and secondary structure similarities within this area between templates and targets. A The secondary structure HAIRPIN LOOP, which exhibits typical characteristics, is depicted along with its quantitative features. B The secondary structure MULTIPLE LOOP, which exhibits another characteristic feature, is depicted along with its corresponding quantitative attributes. C shows the Sequence features of native and predicted RNA binding sites: Motif Structure, Motif Sequence and Motif Set. Among them, Motif Structure is the Position Probability Matrices (PPMs) generated by serialized secondary structure features: B (Bulge), E (External strand), H (Hairpin loop), M (Multiple loop) and S (Stem); Motif set is a sequential description of all binding preference motifs, where each base represents the base enriched in motifsCC BY · PubMed Central
Fig. 3 LS-PEAK on ATF4_ENST00000680748.1 with native seCLIP-seq binding sites. The upper blue histogram shows the base-resolution LS-Score along ATF4_ENST00000680748.1, where the height of each blue bar represents the LS-Score at the corresponding nucleotide position (higher bars indicate higher inferred binding preference). The gray shaded vertical window indicates the LS-PEAK region selected in this example: it is defined as a contiguous segment where LS-Scores exceed the mean LS-Score of this transcript (used here as the cutoff), and it corresponds to the candidate region carried forward for template screening. Protein labels above the histogram (e.g., PRPF39, BUD13) mark the RBPs whose native binding sites are shown for comparison at the corresponding genomic positions. The lower track displays the seCLIP-seq-supported native binding site intervals on the same transcript/locus (shown as the labeled binding segment aligned to the coordinate axis), enabling direct visual comparison between the predicted LS-PEAK window (gray shaded) and the experimentally observed binding locations
Fig. 3 LS-PEAK on ATF4_ENST00000680748.1 with native seCLIP-seq binding sites. The upper blue histogram shows the base-resolution LS-Score along ATF4_ENST00000680748.1, where the height of each blue bar represents the LS-Score at the corresponding nucleotide position (higher bars indicate higher inferred binding preference). The gray shaded vertical window indicates the LS-PEAK region selected in this example: it is defined as a contiguous segment where LS-Scores exceed the mean LS-Score of this transcript (used here as the cutoff), and it corresponds to the candidate region carried forward for template screening. Protein labels above the histogram (e.g., PRPF39, BUD13) mark the RBPs whose native binding sites are shown for comparison at the corresponding genomic positions. The lower track displays the seCLIP-seq-supported native binding site intervals on the same transcript/locus (shown as the labeled binding segment aligned to the coordinate axis), enabling direct visual comparison between the predicted LS-PEAK window (gray shaded) and the experimentally observed binding locationsCC BY · PubMed Central
Fig. 4 Prediction results compared with other methods on different cell lines. MCC of the prediction results of PRIME-BSPre, compared with PRIME-3D2D, PrismNet on the cell line K562 and the cell line HepG2 over 158 RBP-RNA test pairs. The box line plot shows overall results on different methods
Fig. 4 Prediction results compared with other methods on different cell lines. MCC of the prediction results of PRIME-BSPre, compared with PRIME-3D2D, PrismNet on the cell line K562 and the cell line HepG2 over 158 RBP-RNA test pairs. The box line plot shows overall results on different methodsCC BY · PubMed Central
Fig. 5 Comparison with PrismNet on different cell lines. A-B Comparison of PRIME-BSPre with PrismNet in different cell lines. Dot plots depict the performance of all RNAs in each RBP, as predicted by PRIME-BSPre and PrismNet
Fig. 5 Comparison with PrismNet on different cell lines. A-B Comparison of PRIME-BSPre with PrismNet in different cell lines. Dot plots depict the performance of all RNAs in each RBP, as predicted by PRIME-BSPre and PrismNetCC BY · PubMed Central

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Citations

Cites

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Metadata

Authors
Wei, X., Duan, Y., Li, D., Liu, X., Xie, J., & Liu, S.
Affiliations
Huazhong University of Science and Technology (CN)
Corresponding author
Liu, Shiyong
ORCID
Venue
BMC Genomics
Publisher
Springer Science and Business Media LLC
Published
2026-02-21
Volume
27
Issue
1
ISSN
1471-2164 (ISSN-L)
DOI
10.1186/s12864-026-12657-3
PMC
PMC13032426
OpenAlex
W7130849569
Cited by
0
References
3
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Genomics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Natural Science Foundation of China (32271267)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Keywords
RNA-binding proteins, template-based modeling, RNA secondary structure, RNA tertiary structure, RNA motifs, genomic prediction, human genome
MeSH terms
Prediction Algorithms, Algorithms, Binding Sites, Humans, Nucleic Acid Conformation, Protein Binding, RNA, Genome, Human, RNA-Binding Proteins, Computational Biology, Genomics

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