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Related Experiment Video

Updated: Feb 12, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Published on: February 7, 2019

Accurate and sensitive quantification of protein-DNA binding affinity.

Chaitanya Rastogi^1,2, H Tomas Rube^2,3, Judith F Kribelbauer^2,3

¹Department of Applied Physics, Columbia University, New York, NY 10027.

Proceedings of the National Academy of Sciences of the United States of America

|April 4, 2018

Summary

We developed No Read Left Behind (NRLB), a new computational framework to accurately predict where transcription factors bind to DNA. This method helps identify disease-associated genetic variations and understand gene regulation.

Keywords:

SELEX computational modeling enhancer assays low-affinity binding sites transcription factors

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Last Updated: Feb 12, 2026

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Published on: February 7, 2019

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Transcription factors (TFs) regulate gene expression through sequence-specific DNA binding.
Mutations in TF binding sites are linked to human diseases, but prediction methods are limited.

Purpose of the Study:

To develop a robust computational framework for predicting TF binding sites.
To infer biophysical models of protein-DNA recognition and interpret regulatory sequences.

Main Methods:

Developed the No Read Left Behind (NRLB) maximum likelihood framework.
Inferred biophysical models from in vitro selected DNA binding site libraries.
Validated predictions against experimental data for human Max homodimer and p53 tetramer.

Main Results:

NRLB accurately predicts human Max homodimer binding, aligning with experimental measurements.
The framework distinguishes multiple binding modes and captures p53 tetramer specificity.
Newly identified low-affinity enhancer binding sites were confirmed as functional in vivo.

Conclusions:

NRLB provides a powerful paradigm for identifying protein binding sites in eukaryotic genomes.
The framework enables accurate interpretation of gene regulatory sequences and their contribution to gene expression.