Related Experiment Video
Updated: Feb 2, 2026
Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation
Published on: February 12, 2022
RNAct: Protein-RNA interaction predictions for model organisms with supporting experimental data
Benjamin Lang1, Alexandros Armaos1, Gian G Tartaglia1,2,3,4
1Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain.
Abstract:
Protein-RNA interactions are implicated in a number of physiological roles as well as diseases, with molecular mechanisms ranging from defects in RNA splicing, localization and translation to the formation of aggregates. Currently, ∼1400 human proteins have experimental evidence of RNA-binding activity. However, only ∼250 of these proteins currently have experimental data on their target RNAs from various sequencing-based methods such as eCLIP. To bridge this gap, we used an established, computationally expensive protein-RNA interaction prediction method, catRAPID, to populate a large database, RNAct. RNAct allows easy lookup of known and predicted interactions and enables global views of the human, mouse and yeast protein-RNA interactomes, expanding them in a genome-wide manner far beyond experimental data (http://rnact.crg.eu).
Insights
Researchers predict protein-RNA interactions to understand their roles in health and disease. They created RNAct, a database of known and predicted interactions, greatly expanding available data beyond experimental evidence.
Area of Science:
- Molecular biology
- Bioinformatics
- Genomics
Background:
- Protein-RNA interactions are crucial for cellular functions and are implicated in various diseases.
- While ~1400 human proteins are known RNA-binders, experimental data on their specific RNA targets is limited for most (~250 proteins).
- A significant gap exists in understanding the full scope of protein-RNA interactions.
Purpose of the Study:
- To computationally predict and compile a comprehensive database of protein-RNA interactions.
- To expand the knowledge of the protein-RNA interactome beyond experimentally validated data.
- To provide a resource for exploring global protein-RNA interaction networks in multiple species.
Main Methods:
- Utilized the catRAPID computational method for predicting protein-RNA interactions.
- Developed the RNAct database to store and organize predicted and known interaction data.
- Integrated experimental data with computational predictions to create a larger interactome resource.
Main Results:
- The RNAct database was populated with a large number of known and predicted protein-RNA interactions.
- The database provides genome-wide views of protein-RNA interactomes for human, mouse, and yeast.
- RNAct significantly expands the available data on protein-RNA interactions beyond current experimental limitations.
Conclusions:
- The RNAct database serves as a valuable resource for studying protein-RNA interactions.
- Computational predictions can effectively bridge the gap in experimentally derived interaction data.
- RNAct facilitates a deeper understanding of the protein-RNA interactome's role in biological processes and diseases.
Related Concept Videos
01:13Protein Organization
01:24Protein Organization
The primary structure of a protein is its amino acid sequence....
02:36RNA Polymerase II Accessory Proteins
01:23Correlation of Experimental Data
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
02:26Protein Networks
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
02:07Organization of Genes