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RRMScorer: A web server for predicting RNA recognition motif binding preferences.

Adrian Diaz1,2, Joel Roca-Martínez1,2, Wim Vranken1,2

  • 1Interuniversity Institute of Bioinformatics in Brussels, VUB/ULB, Brussels 1050, Belgium.

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RRMScorer predicts RNA binding preferences for RNA recognition motif (RRM) proteins. This web server analyzes protein sequences to reveal how RRMs interact with RNA, aiding mutation studies.

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Structural Biology

Background:

  • RNA recognition motifs (RRMs) are the most common RNA-binding domains in eukaryotes.
  • Understanding RRM-RNA interactions is crucial for deciphering gene regulation and cellular processes.

Purpose of the Study:

  • To develop and present RRMScorer, a web server for predicting RNA binding preferences of RRM-containing proteins.
  • To provide residue-level insights into RRM-RNA interactions and facilitate the study of mutations.

Main Methods:

  • Analysis of 187 RRM-RNA structural complexes.
  • Development of a probabilistic model based on amino acid-nucleotide interaction propensities.
  • Implementation of a user-friendly web server accepting protein sequences and optional RNA sequences.

Main Results:

  • RRMScorer calculates residue-level binding scores for RRM domains.
  • The server provides detailed visualizations, including bar plots and sequence logos.
  • Precomputed predictions for over 1400 RRM proteins are integrated into the server.

Conclusions:

  • RRMScorer offers accurate predictions and residue-level insights into RRM-RNA binding preferences.
  • The tool is valuable for researchers studying RRM function, mutations, and comparative analyses.
  • The freely accessible web server enhances the exploration of RRM-RNA interaction landscapes.