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RMalign: an RNA structural alignment tool based on a novel scoring function RMscore.

Jinfang Zheng1, Juan Xie1, Xu Hong1

  • 1School of Physics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.

BMC Genomics
|April 10, 2019
PubMed
Summary
This summary is machine-generated.

A new RNA 3D structural alignment method, RMalign, uses a size-independent score (RMscore) to improve RNA-protein modeling. This enhancement led to a 10% success rate increase in the PRIME2.0 software for predicting protein-RNA interactions.

Keywords:
Protein-RNA interactionRMalignRMscoreRNA structural alignment

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Predicting RNA-protein 3D complex structures remains a significant challenge in structural biology.
  • Existing template-based methods like PRIME show promise but are limited by size-dependent scoring functions in RNA alignment algorithms.
  • The size-dependency of the SARA scoring function in PRIME can hinder accurate template detection.

Purpose of the Study:

  • To develop a novel RNA 3D structural alignment approach with a size-independent scoring function.
  • To improve the accuracy and success rate of RNA-protein complex structure prediction.
  • To enhance the PRIME software for modeling protein-RNA interactions.

Main Methods:

  • Developed RMalign, a new RNA 3D structural alignment approach utilizing a size-independent scoring function, RMscore.
  • Optimized RMscore parameters using randomly selected RNA pairs and identified phase transition points.
  • Benchmarked RMalign against existing methods like SARA and ESA-RNA using tRNA and balance-FSCOR datasets.

Main Results:

  • RMscore demonstrated higher precision (0.88) compared to SARAscore (0.78) in tRNA benchmarking.
  • RMalign performed comparably to ESA-RNA in balance-FSCOR benchmarking for RNA structural similarity.
  • RMalign significantly outperformed the SARA approach in balance-x-FSCOR benchmarking due to its size-independent scoring.
  • The integration of RMalign into PRIME resulted in PRIME2.0, achieving a 10% improvement in success rate for RNA-protein modeling.

Conclusions:

  • RMalign, based on the size-independent RMscore, is a robust RNA 3D structural alignment tool.
  • The developed RMalign approach has been successfully integrated into PRIME2.0, enhancing its performance.
  • PRIME2.0 offers a valuable tool for the biological community for modeling protein-RNA interactions.