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Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...

Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

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Related Experiment Video

Updated: Sep 5, 2025

PAR-CliP - A Method to Identify Transcriptome-wide the Binding Sites of RNA Binding Proteins

PAR-CliP - A Method to Identify Transcriptome-wide the Binding Sites of RNA Binding Proteins

Published on: July 2, 2010

A web server for identifying circRNA-RBP variable-length binding sites based on stacked generalization ensemble deep

Zhengfeng Wang¹, Xiujuan Lei²

¹School of Computer Science, Shaanxi Normal University, Xi'an 710119, China; College of Information Science and Engineering, Guilin University of Technology, Guilin 541004, China; Guangxi Key Laboratory of Embedded Technology and Intelligent System, Guilin University of Technology, Guilin 541004, China.

Methods (San Diego, Calif.)

|July 10, 2022

Summary

This summary is machine-generated.

This study introduces CirRBP, a deep learning model that accurately predicts RNA-binding protein (RBP) binding sites on circular RNAs (circRNAs) using multiple data sources. The developed CRWS web server provides an accessible tool for precise circRNA-RBP interaction analysis.

Keywords:

Binding sites Circular RNA RNA-binding protein Stacked generalization ensemble

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Area of Science:

Bioinformatics
Computational Biology
Molecular Biology

Background:

Circular RNAs (circRNAs) regulate gene expression through interactions with RNA-binding proteins (RBPs).
Existing computational methods for predicting circRNA-RBP binding sites often rely on single data sources and lack precision in localization.
Accurate identification of specific binding sites is crucial for understanding circRNA function.

Purpose of the Study:

To develop a novel algorithm and deep learning model for precise localization of RBP binding sites on circRNAs.
To integrate multiple data sources for improved prediction accuracy and reliability.
To create a user-friendly web server for analyzing circRNA-RBP interactions.

Main Methods:

Development of a binding site localization algorithm fusing data from multiple databases.
Design of a stacked generalization ensemble deep learning model (CirRBP) for circRNA-RBP binding site identification.
Creation of an open-source web application (CRWS) integrating the CirRBP model and visualization tools.

Main Results:

The CirRBP model demonstrates superior performance compared to individual sub-models and existing prediction tools.
The CRWS web server accurately predicts exact potential RBP binding sites on circRNA sequences.
CRWS can also identify conserved motifs within RBP binding datasets.

Conclusions:

The developed CirRBP model and CRWS web server represent a significant advancement in predicting precise circRNA-RBP binding sites.
CRWS is the first online tool to utilize multi-source data for training models and predicting exact binding sites.
This tool facilitates research into circRNA-RBP interactions and their biological implications.