ArticleProceedings of the National Academy of Sciences of the United States of America2018
Accurate and sensitive quantification of protein-DNA binding affinity.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
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Who cites it
73 citing papers in PubMed.
- An Isogenic Yeast Model Reveals the Influence of Native Promoter G‑Quadruplex Forming Sequences on P53 and NF-κB Transactivation.ACS bio & med chem Au · 2026Article
- Identification of methylation-sensitive human transcription factors using meSMiLE-seq.Nature communications · 2026Article
- A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function.Nature biotechnology · 2026Article
- RGTBind: RBF-gate graph transformer with spatially biased attention for protein-DNA binding-site prediction.Journal of molecular modeling · 2026Article
- Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning.NAR genomics and bioinformatics · 2026Article
- Multimodal bHLH-PAS DNA binding controls specificity and drives obesity.Nucleic acids research · 2026Article
- PRIMED: predicting DNA binding residues by leveraging pre-trained protein language models.Frontiers in artificial intelligence · 2026Article
- Skin-Integrated Soft Wearable XR Interfaces for Seamless and Realistic User Experience.Chemical reviews · 2025Review
- CAP: Commutative algebra prediction of protein-nucleic acid binding affinities.Machine learning: science and technology · 2025Article
- Review
- Predicting the DNA binding specificity of transcription factor mutants using family-level biophysically interpretable machine learning.Nucleic acids research · 2025Article
- Article
- Multisite λ-Dynamics for Protein-DNA Binding Affinity Prediction.Journal of chemical theory and computation · 2025Article
- Interfacial water confers transcription factors with dinucleotide specificity.Nature structural & molecular biology · 2025Article
- Experimental approaches to investigate biophysical interactions between homeodomain transcription factors and DNA.Biochimica et biophysica acta. Gene regulatory mechanisms · 2025Review
- Effective in vivo binding energy landscape illustrates kinetic stability of RBPJ-DNA binding.Nature communications · 2025Article
- Article
- Bioinformatics Approaches for Understanding the Binding Affinity of Protein-Nucleic Acid Complexes.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Article
- Comprehensive Predictions of Mef2-Mediated Chromatin Loops, Which May Inhibit Ubx Binding by Blocking Low-Affinity Binding Sites.Journal of developmental biology · 2024Article
13 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
Abstract
Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.