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Related Concept Videos

Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Conserved Binding Sites01:49

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 analyses the...
Conserved Binding Sites01:49

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 analyses the...

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Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins
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Detecting cis-regulatory binding sites for cooperatively binding proteins.

Liesbeth van Oeffelen1, Pierre Cornelis, Wouter Van Delm

  • 1Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. Liesbeth.vanOeffelen@esat.kuleuven.be

Nucleic Acids Research
|April 11, 2008
PubMed
Summary

This study introduces a novel scoring method for predicting cis-regulatory modules using a physical binding model. It accurately models protein interactions and outperforms existing methods, especially for homotypic cooperativity.

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A Protein Preparation Method for the High-throughput Identification of Proteins Interacting with a Nuclear Cofactor Using LC-MS/MS Analysis
05:43

A Protein Preparation Method for the High-throughput Identification of Proteins Interacting with a Nuclear Cofactor Using LC-MS/MS Analysis

Published on: January 24, 2017

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Predicting cis-regulatory modules (CRMs) is crucial for understanding gene regulation.
  • Current methods often rely on position weight matrices (PWMs) with parameters lacking physical meaning.
  • These parameters are difficult to estimate and limit prediction accuracy.

Purpose of the Study:

  • To develop a novel scoring method for CRM prediction based on a physical protein-DNA binding model.
  • To improve the accuracy of CRM detection by incorporating biophysical principles.
  • To provide a more interpretable and parameter-efficient approach compared to traditional PWM methods.

Main Methods:

  • Developed a scoring method utilizing an underlying physical binding model for protein-DNA interactions.
  • Modeled homotypic cooperative interactions using distances between binding sites and cooperative binding constants.
  • Incorporated parameters for heterotypic cooperative binding, including protein concentration and partition functions.
  • Applied the method to a case study involving the bacterial ferric uptake regulator.

Main Results:

  • The new scoring method significantly outperforms existing PWM-based methods for homotypic cooperatively binding proteins.
  • The physical binding model eliminates the need for additional, non-physical parameters.
  • Accurate modeling of biophysical cooperativity enhances prediction accuracy.
  • Demonstrated superior performance in the ferric uptake regulator case study.

Conclusions:

  • The developed physical binding model offers a more accurate and interpretable approach to cis-regulatory module prediction.
  • This method advances the field by integrating biophysical principles into computational genomics.
  • It provides a robust framework for analyzing complex protein-DNA interactions in gene regulation.