RRMScorer

RRMScorer predicts interactions between RNA recognition motifs (RRMs) and single-stranded RNA from amino acid and nucleotide sequences to estimate binding preferences and affinities.

Key Features:

• Sequence-Based Predictions: Predicts RRM–RNA interactions solely from amino acid and nucleotide sequences.
• Computational Scoring Method: Employs a computational scoring method derived from analysis of structural data to estimate binding affinities between RRMs and single-stranded RNA.
• RNA Recognition Code Derivation: Predicts RNA sequence motifs and aids in elucidating an RNA recognition code for canonical RRMs through computational analyses.

Scientific Applications:

• Structural Analysis of RRM-RNA Complexes: Leverages experimentally determined RRM–RNA structures to investigate the structural basis of RRM specificity and affinity.
• Design of RNA Binding Motifs: Assists design of RNA-binding motifs and tailored RRMs for applications such as modulating gene expression or targeting viral RNAs.
• Synthetic Biology Applications: Enables design of RRMs with specified RNA recognition properties for synthetic biology and biotechnological uses.

Methodology:

Uses a computational scoring approach based on in-depth analysis of structural data and a carefully curated multiple sequence alignment to estimate RRM binding preferences and affinities for single-stranded RNA.