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Updated: Feb 19, 2026

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Published on: August 9, 2019

Performing SELEX experiments in silico.

J A J Wondergem¹, H Schiessel¹, M Tompitak¹

¹Institute Lorentz for Theoretical Physics, Leiden University, Niels Bohrweg 2, 2333 CA Leiden, The Netherlands.

The Journal of Chemical Physics

|November 10, 2017

Summary

This summary is machine-generated.

Computational tools can now emulate DNA sequence selection experiments, offering insights into protein-DNA interactions and enabling studies of challenging DNA structures like rings.

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Area of Science:

Computational biology
Biophysics
Molecular dynamics

Background:

DNA elasticity is sequence-dependent, influencing protein-DNA complex formation and DNA structural preferences.
Systematic Evolution of Ligands by EXponential enrichment (SELEX) experiments identify DNA sequence preferences for entities like nucleosomes and DNA rings.

Purpose of the Study:

To demonstrate the emulation of SELEX experiments using computational and theoretical tools.
To enhance understanding of simulation parameters (temperature, selection pressure) and model predictions.
To enable in silico studies of experimentally challenging DNA systems.

Main Methods:

Utilized recently developed computational and theoretical tools for in silico emulation of sequence selection experiments.
Employed a rigid base-pair model to predict DNA sequence preferences.
Simulated DNA rings and other potentially high-cost DNA structures.

Main Results:

Achieved agreement between the rigid base-pair model's predictions and experimental results for DNA rings.
Identified discrepancies between model predictions and experimental data, highlighting open research questions.
Successfully applied SELEX methodology in silico to systems difficult to study experimentally, such as short or overwound DNA rings.

Conclusions:

In silico emulation of SELEX experiments provides valuable insights into DNA sequence preferences and biophysical models.
Computational approaches facilitate the study of DNA systems that are experimentally inaccessible or costly.
This methodology advances our understanding of DNA-protein interactions and DNA structural dynamics.